Method and system for improving machine and system that automate execution of distributed ledger and other transaction in spot and forward market for energy, compute, storage and other resource

Abstract

To provide a flexible and intelligent energy / computer facility, an intelligent energy / computer resource management system, a method and an apparatus which are adjusted for uncertainty and variability.SOLUTION: Systems for improving machines and systems that automate execution of distributed ledger and other transactions in spot and forward markets for energy, compute, storage and other resources are disclosed herein. An apparatus includes a robotic process automation circuit 9074 to interpret information from a plurality of data sources, and to interface with a plurality of management applications. The plurality of management applications may each be associated with a separate one of a plurality of financial entities. The robotic process automation circuit may also include an artificial intelligence circuit to improve a process of at least one of the plurality of management applications in response to the information from the plurality of data sources.SELECTED DRAWING: Figure 90

Description

[Technical field]

[0001] This application is a joint venture between U.S. Provisional Patent Application No. 62 / 751,713, filed on October 29, 2018 and entitled “METHODS AND SYSTEMS FOR IMPROVING MACHINES AND SYSTEMS THAT AUTOMATE EXECUTION OF DISTRIBUTED LEDGER AND OTHER TRANSACTIONS IN SPOT AND FORWARD MARKETS FOR ENERGY, COMPUTE, STORAGE AND OTHER RESOURCES” (Attorney Docket No. SFTX-0003-P01), and U.S. Provisional Patent Application No. 62 / 751,713, filed on May 6, 2019 and entitled “ADAPTIVE INTELLIGENCE AND SHARED INFRASTRUCTURE LENDING TRANSACTION ENABLEMENT PLATFORM WITH ROBOTIC PROCESS U.S. Provisional Patent Application No. 62 / 843992 (Attorney Docket No. SFTX-0005-P01), filed on March 13, 2019, entitled “ROBOTIC PROCESS AUTOMATION ARCHITECTURE,”No. 62 / 843,455, filed on May 5, 2019 (Attorney Docket No. SFTX-0007-P01), entitled “ADAPTIVE INTELLIGENCE AND SHARED INFRASTRUCTURE LENDING TRANSACTION ENABLEMENT PLATFORM WITH ROBOTIC PROCESS ARCHITECTURE” and U.S. Provisional Patent Application No. 62 / 818,100, filed on May 5, 2019 (Attorney Docket No. SFTX-0006-P01), entitled “ADAPTIVE INTELLIGENCE AND SHARED INFRASTRUCTURE LENDING TRANSACTION ENABLEMENT PLATFORM WITH ROBOTIC PROCESS ARCHITECTURE” and U.S. Provisional Patent Application No. 62 / 818,100, filed on May 5, 2019 (Attorney Docket No. SFTX-0006-P01), entitled “ADAPTIVE INTELLIGENCE AND SHARED INFRASTRUCTURE LENDING TRANSACTION ENABLEMENT PLATFORM WITH ROBOTIC PROCESS ARCHITECTURE” This application claims the benefit of U.S. Provisional Patent Application No. 62 / 843,456 (Attorney Docket No. SFTX-0008-P01), entitled "METHOD AND SYSTEM FOR USE IN A COMPONENT ARCHITECTURE."

[0002] This application claims the benefit of priority to, and is a continuation-in-part of, International Application No. PCT / US2019 / 030934, filed May 6, 2019, and entitled "METHODS AND SYSTEMS FOR IMPROVING MACHINES AND SYSTEMS THAT AUTOMATE EXECUTION OF DISTRIBUTED LEDGER AND OTHER TRANSACTIONS IN SPOT AND FORWARD MARKETS FOR ENERGY, COMPUTE, STORAGE AND OTHER RESOURCES" (Attorney Docket No. SFTX-0004-WO). International Application No. PCT / US2019 / 030934 (Attorney Docket No. SFTX-0004-WO) is a copy of U.S. Provisional Patent Application No. 62 / 787,206 (Attorney Docket No. SFTX-0001-P01), filed on December 31, 2018 and entitled “METHODS AND SYSTEMS FOR IMPROVING MACHINES AND SYSTEMS THAT AUTOMATE EXECUTION OF DISTRIBUTED LEDGER AND OTHER TRANSACTIONS IN SPOT AND FORWARD MARKETS FOR ENERGY, COMPUTE, STORAGE AND OTHER RESOURCES” and U.S. Provisional Patent Application No. 62 / 787,206 (Attorney Docket No. SFTX-0001-P01), filed on October 29, 2018 and entitled “METHODS AND SYSTEMS FOR IMPROVING MACHINES AND SYSTEMS THAT AUTOMATE EXECUTION OF DISTRIBUTED LEDGER AND OTHER TRANSACTIONS IN SPOT AND FORWARD MARKETS FOR ENERGY, COMPUTE, STORAGE AND OTHER RESOURCES.” This application claims the benefit of priority to U.S. Provisional Patent Application No. 62 / 751,713, entitled "MARKETS FOR ENERGY, COMPUTE, STORAGE AND OTHER RESOURCES" (Attorney Docket No. SFTX-0003-P01).

[0003] Each of the aforementioned applications is incorporated herein by reference in its entirety. [Background technology]

[0004] As machines or automated agents become increasingly involved in market activities, including data gathering, forecasting, planning, and executing trades, including increasingly sophisticated systems such as those used for high-speed trading, there is a need for methods and systems to improve the machines that enable markets, including by increasing the efficiency, speed, and reliability of market participants.

[0005] Many markets are increasingly becoming decentralized rather than centralized, with distributed ledgers like blockchain, peer-to-peer interaction models, and microtransactions replacing or complementing traditional models with centralized authorities and intermediaries. Improved machinery is needed that allows decentralized transactions to take place at scale between many participants, including human participants and automated agents.

[0006] In the operation of blockchains, including cryptocurrencies, energy-intensive computations, such as the calculation of very large hash functions for an ever-growing blockchain, are increasing. In systems using proof-of-work or proof-of-stake, "mining" is carried out, which applies computer processing power on a large scale, to perform calculations that support collective trust in transactions recorded in the blockchain.

[0007] For example, large neural networks with many interconnections operate on many inputs to generate one or more outputs, such as predictions, classifications, optimizations, or control outputs.

[0008] Additionally, the growth of the Internet of Things and cloud computing platforms has led to a proliferation of devices, applications, and the connections between them, and data centers, which house servers and other IT components, account for a significant portion of energy consumption in the United States and other developed countries.

[0009] In this context, energy consumption has become a major factor in the use of computing resources, and energy resources and computing resources (or simply "energy and computing") begin to merge from various perspectives, such as input, activity, output, request, purchase, provisioning, configuration, management, etc. For example, there are projects to place large-scale computing resource facilities for mining cryptocurrencies such as Bitcoin near large hydroelectric power plants such as Niagara Falls.

[0010] A major challenge for facility owners and operators is the uncertainty associated with optimizing their facilities due to, for example, fluctuations in the cost and availability of inputs (especially when less stable renewable resources are involved), fluctuations in the cost and availability of computing and networking resources (e.g., as networks fluctuate in performance), and volatility and uncertainty in the various end markets to which energy and computational resources can be applied (e.g., volatility of cryptocurrencies, volatility of energy markets, volatility of prices in various other markets, uncertainty about the usefulness of artificial intelligence in a wide range of applications, etc.). Summary of the Invention [Problem to be solved by the invention]

[0011] There is a need for flexible and intelligent energy and computing equipment and intelligent energy and computing resource management systems that respond to and adjust to uncertainty and variability, including systems that have the ability to collect, store, and process data, automatically configure inputs, resources, and outputs, and train artificial intelligence / machine learning systems on training sets of equipment results, equipment parameters, and data collected from data sources to optimize various relevant parameters of such equipment. [Means for solving the problem]

[0012] Machine learning potentially enables automated markets, or allows machines interacting with automated markets to develop understanding and execute trades based on predictions, such as participating in forward markets for energy, computation, advertising, etc., based on IoT data, social network data, and other non-traditional data sources. Blockchain and cryptocurrency may support a variety of automated transactions, and the intersection of blockchain and AI may enable a fundamentally different trading infrastructure. As energy is increasingly used for computation, this will enable machines to efficiently allocate available energy resources between storage, computation, and base tasks. These and other concepts are addressed by the methods and systems disclosed herein.

[0013] The present invention provides a method and system that improves the efficiency, speed, reliability, and other aspects of market enabling mechanisms for market participants.

[0014] The present invention provides an improved mechanism for enabling large-scale decentralized trading among multiple participants, including human participants and automated agents.

[0015] Transactions described herein may include financial transactions using various forms of currency, such as government-backed fiat currency, cryptocurrency, tokens, or points (such as loyalty or reward points offered by airlines, hospitality providers, and many other businesses). Transactions may also be understood to encompass a wide range of other transactions involving the exchange of value, including in-kind transactions involving the exchange of resources. Transactions include the exchange of various types of currency, including the exchange of currency for in-kind resources. Resources exchanged may include goods, services, computational resources, energy resources, network bandwidth resources, natural resources, and the like. Transactions may also include the involvement of attention resources by a prospective counterparty in the transaction, such as a consumer of goods, services, and the like, who may be a human being or, in some circumstances, other consumers, such as intelligent (e.g., AI-based agents). Energy optimization for computing, networking and tasks

[0016] In an embodiment, a transaction enabling platform is provided having machines equipped with renewable energy facilities that optimizes the allocation of distribution of generated energy between computational tasks, network tasks and energy consuming tasks.

[0017] In an embodiment, a platform is provided that has the machinery to automatically purchase energy in the energy futures market and enables trading.

[0018] In an embodiment, a trading-enabling platform is provided that has the facility to automatically purchase energy credits in the forward market.

[0019] In an embodiment, a platform is provided that enables trading with a fleet of machines that automatically aggregates purchases in the energy futures markets.

[0020] In an embodiment, a fleet of machines is provided to automatically aggregate the purchase of energy credits in the forward market as a platform to enable trading.

[0021] In an embodiment, a trading-enabling platform is provided that has machines that automatically purchase allocations of spectrum, which is the forward market for network spectrum.

[0022] In an embodiment, a trading enabling platform is provided having machines that automatically sell computing power in the forward market for computing power.

[0023] In an embodiment, a platform is provided that has machines that automatically sell computing storage capacity in a forward market for storage capacity, enabling trading.

[0024] In an embodiment, a platform is provided that has machinery for automatically selling and enabling transactions on the forward market for storage capacity.

[0025] In an embodiment, a platform is provided that enables trading with a machine that automatically sells network bandwidth in a futures market for network capacity.

[0026] In an embodiment, a trading-enabling platform is provided that has a fleet of machines that automatically purchase spectrum allocations, which is a forward market for network spectrum.

[0027] In an embodiment, a platform is provided that enables transactions and has a fleet of machines that automatically optimizes energy usage for the allocation of computational tasks (e.g., mining bitcoins).

[0028] In an embodiment, a platform is provided that enables trading with a fleet of machines that automatically aggregate data to collectively optimize energy forward market purchases.

[0029] In an embodiment, a platform is provided that enables trading with a fleet of machines that automatically aggregates data to collectively optimize forward market purchases of energy credits.

[0030] In an embodiment, a trading-enabling platform is provided that has machines that automatically aggregate data to collectively optimize forward market purchases of network spectrum.

[0031] In an embodiment, a platform is provided that enables trading with a fleet of machines that automatically aggregates data related to the collective optimization of forward market sales of computing capacity.

[0032] In an embodiment, a platform is provided that has machinery for automatically purchasing energy in the energy spot market and enables trading.

[0033] In an embodiment, a trading enabling platform is provided that has the machinery to automatically purchase energy credits in the spot market.

[0034] In an embodiment, a trading enabling platform is provided that has a fleet of machines that automatically aggregates spot market purchases of energy.

[0035] In an embodiment, a platform is provided that enables trading with a fleet of automated counting machines for purchasing energy credits on the spot market.

[0036] In an embodiment, a platform is provided that enables trading with machinery for automatically purchasing allocations of spectrum, which is a spot market for network spectrum.

[0037] In an embodiment, a trading-enabling platform is provided that has a fleet of machines that automatically purchase allocations of spectrum, which is a spot market for network spectrum.

[0038] In an embodiment, a platform is provided that enables transactions and has a fleet of machines that automatically optimizes energy usage for the allocation of computational tasks (e.g., mining bitcoins).

[0039] In an embodiment, a platform is provided that enables trading with a fleet of machines that automatically aggregate data to collectively optimize energy spot market purchases.

[0040] In an embodiment, a platform is provided that enables trading with a fleet of machines that automatically aggregates data to collectively optimize spot market purchases of energy credits.

[0041] In an embodiment, a trading enabling platform is provided that has a fleet of machines that automatically aggregate data to collectively optimize spot market purchases of network spectrum.

[0042] In an embodiment, a platform is provided that has a fleet of machines that automatically sells computing power in the forward market for computing power, enabling trading.

[0043] In an embodiment, a platform is provided that has a fleet of machines that automatically sells computing storage capacity in the forward market for storage capacity and enables trading.

[0044] In an embodiment, a platform is provided that has a fleet of machines that automatically sells storage capacity in the forward market for storage capacity and enables trading.

[0045] In an embodiment, a trading-enabling platform is provided that has a fleet of machines that automatically sell aggregates of network bandwidth in a futures market for network capacity.

[0046] In an embodiment, a trading enabling platform is provided having a machine that automatically forecasts forward market prices for energy prices based on information collected from social media data sources.

[0047] In an embodiment, a trading-enabling platform is provided having a machine that automatically forecasts forward market prices for network spectrum based on information collected from social media data sources.

[0048] In an embodiment, a trading enabling platform is provided that has a machine that automatically forecasts the forward market price of energy credits based on information collected from social media data sources.

[0049] In an embodiment, a trading enabling platform is provided having a machine that automatically predicts the future market value of computing power based on information collected from social media data sources.

[0050] In an embodiment, a platform is provided that enables trading with machines that automatically execute arbitrage strategies for buying and selling computing power by testing the spot market for computing power with small transactions and then rapidly executing larger transactions based on the results of the small transactions.

[0051] In an embodiment, a trading-enabling platform is provided having a machine that automatically executes an arbitrage strategy for buying and selling energy storage capacity by testing the spot market for computing power with small transactions and rapidly executing large transactions based on the results of the small transactions.

[0052] In an embodiment, a platform is provided that enables trading with machines to automatically execute arbitrage strategies for buying and selling network spectrum and bandwidth by testing spot markets for computing power with small transactions and then rapidly executing larger transactions based on the results of the small transactions.

[0053] In an embodiment, a platform is provided that enables transactions with machines that automatically execute arbitrage strategies for buying and selling energy.

[0054] In an embodiment, a trading enabling platform is provided having machines that automatically execute arbitrage strategies for buying or selling energy credits by testing the spot market for computing capacity with small transactions and then rapidly executing larger transactions based on the results.

[0055] In an embodiment, a transaction enabling platform is provided having machines that automatically allocate energy capacity between core tasks, compute tasks, energy storage tasks, data storage tasks, and network tasks.

[0056] In an embodiment, a transaction enabling platform is provided having machines that automatically allocate computing power between core tasks, compute tasks, energy storage tasks, data storage tasks, and network tasks.

[0057] In an embodiment, a transaction enabling platform is provided having machines that automatically allocate network capacity between core tasks, compute tasks, energy storage tasks, data storage tasks, and networking tasks.

[0058] In an embodiment, a transaction-enabling platform is provided having a fleet of machines that automatically allocates collective energy capacity between core tasks, compute tasks, energy storage tasks, data storage tasks, and networking tasks.

[0059] In an embodiment, a transaction-enabling platform is provided that has a fleet of machines that automatically allocates collective computing power between core tasks, computational tasks, energy storage tasks, data storage tasks, and network tasks.

[0060] In an embodiment, a transaction-enabling platform is provided having a fleet of machines that automatically allocates collective network capacity between core tasks, computational tasks, energy storage tasks, data storage tasks, and network tasks. Blockchain for knowledge

[0061] In an embodiment, a platform is provided that has a distributed ledger-based smart contract wrapper, where smart contracts embed IP license terms for intellectual property embedded in the distributed ledger, and perform operations on the distributed ledger to provide access to the intellectual property and enable transactions by the actor committing to the IP license terms.

[0062] In embodiments, a platform is provided that enables transactions with a distributed ledger for aggregating intellectual property licensing terms, where a smart contract wrapper on the distributed ledger enables intellectual property to be added to the aggregated stack of intellectual property via operations on the ledger.

[0063] In an embodiment, a platform is provided that has a distributed ledger for aggregating intellectual property licensing terms, and a smart contract wrapper on the distributed ledger allows operations on the ledger to add intellectual property and agree on the allocation of royalties between the parties in the ledger to enable transactions.

[0064] In embodiments, a platform is provided that enables transactions with a distributed ledger for aggregating intellectual property licensing terms, where a smart contract wrapper on the distributed ledger enables intellectual property to be added to the aggregated stack of intellectual property via operations on the ledger.

[0065] In embodiments, a platform is provided that enables transactions having a distributed ledger for aggregating intellectual property license terms, and where smart contract rappers on the distributed ledger can commit parties to contract terms with operations on the ledger.

[0066] In an embodiment, a platform is provided that has a distributed ledger that tokenizes an instruction set, where operations on the distributed ledger provide provable access to the instruction set, thereby enabling transactions.

[0067] In an embodiment, a platform is provided that has a distributed ledger that tokenizes executable algorithmic logic, where operations on the distributed ledger provide provable access to the executable algorithmic logic, thereby enabling transactions.

[0068] In an embodiment, a platform is provided that has a distributed ledger that tokenizes the instruction set of a 3D printer and enables transactions by providing provable access to the instruction set through operations on the distributed ledger.

[0069] In an embodiment, a platform is provided that enables transactions with a distributed ledger that tokenizes an instruction set for a coating process, with operations on the distributed ledger providing provable access to the instruction set.

[0070] In an embodiment, a platform is provided that has a distributed ledger that tokenizes the instruction set of a semiconductor manufacturing process and enables transactions by providing provable access to the manufacturing process through operations on the distributed ledger.

[0071] In an embodiment, a platform is provided that has a distributed ledger that tokenizes firmware programs and enables transactions where operations on the distributed ledger allow provable access to the firmware programs.

[0072] In an embodiment, a platform is provided that has a distributed ledger that tokenizes the instruction set of the FPGA, where operations on the distributed ledger provide provable access to the FPGA, thereby enabling transactions.

[0073] In an embodiment, a platform is provided that has a distributed ledger that tokenizes serverless code logic and enables transactions where operations on the distributed ledger provide provable access to the serverless code logic.

[0074] In an embodiment, a platform is provided that enables transactions with a distributed ledger that tokenizes the instruction set of a crystal production system, with provable access to the instruction set through operations on the distributed ledger.

[0075] In an embodiment, a platform is provided that has a distributed ledger that tokenizes an instruction set for a food preparation process, where operations on the distributed ledger provide provable access to the instruction set, thereby enabling transactions.

[0076] In an embodiment, a platform is provided that has a distributed ledger that tokenizes the instruction set of a polymer manufacturing process and enables transactions by providing provable access to the instruction set through operations on the distributed ledger.

[0077] In an embodiment, a platform is provided that has a distributed ledger that tokenizes an instruction set for a chemical synthesis process and enables transactions by providing provable access to the instruction set through operations on the distributed ledger.

[0078] In an embodiment, a platform is provided that has a distributed ledger that tokenizes the instruction set of a biological production process and provides provable access to the instruction set through operations on the distributed ledger, thereby enabling transactions.

[0079] In an embodiment, a platform is provided that enables transactions having a distributed ledger that tokenizes trade secrets with an expert wrapper, where operations on the distributed ledger provide provable access to the trade secrets, and where the wrapper provides expert verification of the trade secrets.

[0080] In an embodiment, a platform for enabling transactions is provided that comprises a distributed ledger that aggregates views of trade secrets onto a chain that provides proof of which parties have viewed the trade secrets and how.

[0081] In an embodiment, a platform is provided that enables transactions having a distributed ledger that tokenizes an instruction set, where operations on the distributed ledger provide provable access to the instruction set, and execution of the instruction set on the system leads to the recording of a transaction on the distributed ledger.

[0082] In an embodiment, a transaction enabling platform is provided having a distributed ledger that tokenizes items of intellectual property and a reporting system that reports analytics based on operations performed on the distributed ledger and the intellectual property.

[0083] In an embodiment, a platform is provided that has a distributed ledger that aggregates a set of instructions and enables transactions by adding at least one instruction to an existing set of instructions to provide a modified set of instructions through operations on the distributed ledger. Intelligent Cryptocurrency

[0084] In an embodiment, a trading enabling platform is provided having a smart wrapper for cryptocurrency coins that directs execution of transactions involving the coins to a geographic location based on tax treatment of the coin and / or transaction in the geographic location.

[0085] In an embodiment, a trading enabling platform is provided having a smart wrapper for cryptocurrency coins that directs execution of transactions involving the coins to a geographic location based on tax treatment of the coin and / or transaction in the geographic location.

[0086] In an embodiment, a platform is provided that enables transactions with self-executing cryptocurrency coins that commit transactions upon recognition of location-based parameters that provide favorable tax treatment.

[0087] In an embodiment, a trading enabling platform is provided having an expert system that utilizes machine learning to optimize the execution of cryptocurrency transactions based on tax status.

[0088] In an embodiment, a trading enabling platform is provided that aggregates regulatory information covering cryptocurrency transactions and has an expert system that automatically selects a jurisdiction for operation based on the regulatory information.

[0089] In an embodiment, a platform for enabling transactions is provided having an expert system that uses machine learning to optimize the execution of cryptocurrency transactions based on real-time energy price information of available energy sources.

[0090] In an embodiment, a platform for enabling transactions is provided having an expert system that uses machine learning to optimize the execution of cryptocurrency transactions based on an understanding of available energy sources for powering computing resources for executing the transactions.

[0091] In an embodiment, a trading enabling platform is provided having an expert system that uses machine learning to optimize the charging and recharging cycles of a rechargeable battery system to provide the energy required to execute cryptocurrency transactions. Forecasting forward markets using non-traditional data

[0092] In an embodiment, a trading enabling platform is provided having an expert system that predicts forward market prices in a market based on understanding gained from analyzing Internet of Things data sources and executes trades based on the forward market prediction.

[0093] In an embodiment, a trading enabling platform is provided having an expert system that predicts forward market prices in a market based on understanding gained from analyzing social network data sources and executes trades based on the forward market predictions.

[0094] In an embodiment, a trading-enabling platform is provided having an expert system that predicts forward market prices in a market based on understanding gained from analyzing Internet of Things (IoT) data sources and executes cryptocurrency transactions based on the forward market predictions.

[0095] In an embodiment, a trading enabling platform is provided having an expert system that predicts forward market prices in a market based on understanding gained from analyzing social network data sources and executes cryptocurrency transactions based on the forward market prediction.

[0096] In an embodiment, a trading enabling platform is provided having an expert system that forecasts forward market prices for energy markets based on understanding gained from analyzing Internet of Things data sources and executes trades based on the forward market forecasts.

[0097] In an embodiment, a trading enabling platform is provided having an expert system that forecasts forward market prices for energy markets based on understanding gained from analyzing social network data sources and executes trades based on the forward market forecasts.

[0098] In an embodiment, a transaction enabling platform is provided having an expert system that predicts forward market prices in a market for computing resources based on understanding gained from analyzing Internet of Things data sources and executes transactions based on the forward market predictions.

[0099] In an embodiment, a platform for enabling transactions is provided having an expert system that forecasts forward market prices in a spectrum or network bandwidth market based on understanding gained from analyzing Internet of Things data sources and executes transactions based on the forward market forecast.

[0100] In an embodiment, a transaction enabling platform is provided having an expert system that predicts forward market prices in a market for computing resources based on understanding gained from analyzing social network data sources and executes transactions based on the forward market predictions.

[0101] In an embodiment, a transaction enabling platform is provided having an expert system that predicts forward market prices in a market for advertising based on understanding gained from analyzing Internet of Things data sources and executes transactions based on the forward market predictions.

[0102] In an embodiment, a transaction enabling platform is provided having an expert system that predicts forward market prices in a market for advertising based on understanding gained from analyzing social network data sources and executes transactions based on the forward market predictions.

[0103] In an embodiment, a trading enabling platform is provided having a machine that automatically forecasts forward market prices for energy prices based on information collected from automated agent behavioral data sources.

[0104] In an embodiment, a trading-enabling platform is provided having a machine that automatically forecasts forward market prices for network spectrum based on information collected from automated agent behavioral data sources.

[0105] In an embodiment, a trading enabling platform is provided having a machine that automatically forecasts forward market prices for energy credits based on information collected from automated agent behavioral data sources.

[0106] In an embodiment, a trading enabling platform is provided having a machine that automatically forecasts forward market value of computing power based on information collected from automated agent behavioral data sources.

[0107] In an embodiment, a trading enabling platform is provided having a machine that automatically forecasts forward market prices for energy prices based on information collected from behavioral data sources of business entities.

[0108] In an embodiment, a trading enabling platform is provided having a machine that automatically forecasts forward market prices for network spectrum based on information collected from business entity behavioral data sources.

[0109] In an embodiment, a trading enabling platform is provided having a machine that automatically forecasts forward market prices for energy credits based on information collected from behavioral data sources of business entities.

[0110] In an embodiment, a trading enabling platform is provided having a machine that automatically forecasts a forward market value of computing power based on information collected from behavioral data sources of business entities.

[0111] In an embodiment, a trading enabling platform is provided that has machines automatically forecasting forward market prices for energy prices based on information collected from human behavioral data sources.

[0112] In an embodiment, a trading-enabling platform is provided having a machine-based, automated forecasting of forward market prices for network spectrum based on information collected from human behavioral data sources.

[0113] In an embodiment, a trading enabling platform is provided that has machines automatically forecasting forward market prices for energy credits based on information collected from human behavioral data sources.

[0114] In an embodiment, a trading enabling platform is provided that has machines automatically forecasting the forward market value of computing power based on information collected from human behavioral data sources.

[0115] In an embodiment, a transaction enabling platform is provided having an expert system that forecasts forward market prices in spectrum and / or network bandwidth markets based on understanding gained from analyzing social data sources and executes transactions based on the forward market forecasts.

[0116] In an embodiment, a platform for enabling trading is provided having an intelligent agent configured to solicit attention resources of another external intelligent agent.

[0117] In an embodiment, a trading-enabling platform is provided with machines that automatically purchase attention resources in the forward market for attention.

[0118] In an embodiment, a platform is provided that has a fleet of machines that automatically aggregates purchases in the forward market of interest and enables trading.

[0119] Provided herein are flexible and intelligent energy and computing facilities, and intelligent energy and computing facility resource management systems, including components, systems, services, modules, programs, processes and other enabling elements such as functionality for data collection, storage and processing; automatic configuration of inputs, resources and outputs; and functionality for training an artificial intelligence / machine learning system to optimize parameters associated with such facility by learning on a training set of facility outcomes, facility parameters, and data collected from data sources.

[0120] In an embodiment, provided herein is an information technology system for providing data to an intelligent energy and computing facility resource management system having a system for learning with a training set of facility outcomes, facility parameters, and data collected from data sources to train an artificial intelligence / machine learning system to predict likely production outcomes of the facility.

[0121] In an embodiment, provided herein is an information technology system for providing data to an intelligent energy and computing facility resource management system having a system that learns with a training set of facility production outcomes, facility parameters, and data collected from data sources to train an artificial intelligence / machine learning system to predict facility production outcomes.

[0122] In an embodiment, provided herein is an information technology system for providing data to an intelligent energy and computing facility resource management system having a system that learns with a training set of facility outcomes, facility parameters, and data collected from data sources to train an artificial intelligence / machine learning system to optimize the provisioning and allocation of energy and computing resources to generate a preferred facility resource utilization profile among a set of available profiles.

[0123] In an embodiment, provided herein is an information technology system for providing data to an intelligent energy and computing facility resource management system having a system that learns with a training set of facility outcomes, facility parameters, and data collected from data sources, and training an artificial intelligence / machine learning system to optimize the provisioning and allocation of energy and computing resources to generate a preferred facility resource output selection among a set of available outputs.

[0124] In an embodiment, provided herein is an information technology system for providing data to an intelligent energy and computational facility resource management system having a system that learns with a training set of facility outcomes, facility parameters, and data collected from data sources, and can train the artificial intelligence / machine learning system to optimize the request and provisioning of available energy and computational resources to generate a preferred facility input resource profile among a set of available profiles.

[0125] In an embodiment, provided herein is an information technology system for providing data to an intelligent energy and computing facility resource management system having a system that learns with a training set of facility outcomes, facility parameters, and data collected from data sources, to train an artificial intelligence / machine learning system to optimize the configuration of available energy and computing resources to generate a preferred facility resource configuration profile among a set of available profiles.

[0126] In an embodiment, provided herein is an information technology system for providing data to an intelligent energy and computing facility resource management system having a system that learns with a training set of facility outcomes, facility parameters, and data collected from data sources, and an information technology system for training an artificial intelligence / machine learning system to optimize selection and configuration of artificial intelligence systems to generate a preferred facility output profile among a set of available artificial intelligence systems and configurations.

[0127] In an embodiment, provided herein is an information technology system for providing data to an intelligent energy and computing facility resource management system having a system that learns with a training set of facility outcomes, facility parameters, and data collected from data sources, and trains the artificial intelligence / machine learning system to generate an indication that current or potential customers should be contacted regarding outputs that can be provided by the facility.

[0128] In an embodiment, the present specification provides a system having an intelligent and flexible energy and computing facility, wherein an artificial intelligence / machine learning system configures the facility from a set of available configurations based on a set of detected conditions related to at least one of input resources, facility resources, output parameters, and external conditions related to the output of the facility.

[0129] In an embodiment, the present specification provides a system having an intelligent and flexible energy and computing facility whereby an artificial intelligence / machine learning system configures the facility among a set of available configurations based on a set of detected conditions associated with a set of input resources.

[0130] In an embodiment, the present specification provides a system having an intelligent and flexible energy and computing facility whereby an artificial intelligence / machine learning system configures the facility from among a set of available configurations based on a set of detected conditions associated with a set of facility resources.

[0131] In an embodiment, the present specification provides a system having an intelligent and flexible energy and computing facility whereby an artificial intelligence / machine learning system configures the facility from a set of available configurations based on a set of detected conditions related to output parameters.

[0132] In an embodiment, the present specification provides a system having an intelligent and flexible energy and computing facility whereby an artificial intelligence / machine learning system configures the facility from a set of available configurations based on a set of detected conditions related to utilization parameters on the output of the facility.

[0133] In an embodiment, the present specification provides a system having an intelligent, flexible energy and computing facility, where an artificial intelligence / machine learning system configures the facility from a set of available configurations based on a set of parameters received from a digital twin for the facility.

[0134] The present disclosure and the following detailed description of certain embodiments thereof can be understood with reference to the following figures. [Brief description of the drawings]

[0135] [Figure 1]FIG. 1 is a schematic diagram of components of a platform for enabling intelligent trading in accordance with an embodiment of the present disclosure.

[0136] [Figure 2A] 2A-2B are schematic diagrams of additional components of a platform for enabling intelligent transactions in accordance with an embodiment of the present disclosure. [Figure 2B] 2A-2B are schematic diagrams of additional components of a platform for enabling intelligent transactions in accordance with an embodiment of the present disclosure.

[0137] [Diagram 3] FIG. 3 is a schematic diagram of additional components of a platform for enabling intelligent trading in accordance with an embodiment of the present disclosure.

[0138] [Figure 4] 4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Diagram 5] 4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Figure 4]4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Figure 6] 4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Figure 7] 4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Figure 8] 4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Figure 9]4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Figure 10] 4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Figure 11] 4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Figure 12] 4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting autonomous control, and for other purposes. [Figure 13]4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Figure 14] 4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Figure 15] 4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Figure 16] 4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Figure 17]4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Figure 18] 4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Figure 19] 4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Figure 20] 4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Figure 21]4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Figure 22] 4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Diagram 23] 4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Figure 24] 4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Diagram 25]4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Figure 26] 4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Figure 27] 4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Figure 28] 4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Figure 29]4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Diagram 30] 4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes. [Diagram 31] 4 through 31 are schematic diagrams of embodiments of neural net systems connected to, integrated into, and accessible from the platform to enable intelligent trading, including expert systems, self-organization, machine learning, and artificial intelligence, in accordance with embodiments of the present disclosure, showing neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, assisting in autonomous control, and for other purposes.

[0139] [Diagram 32] FIG. 32 is a schematic diagram of components of an environment including an intelligent energy and computing facility, a host intelligent energy and computing facility resource management platform, a set of data sources, a set of expert systems, a set of marketplace platforms and interfaces to external resources, and a set of user or client systems and devices in accordance with an embodiment of the present disclosure.

[0140] [Diagram 33] Figure 33 shows the components and interactions of the system that enable trading, finance and the marketplace.

[0141] [Diagram 34] Figure 34 shows the components and interactions of a series of data processing layers in a system that enables transactions, finance, and marketplaces.

[0142] [Diagram 35] Figure 35 illustrates the adaptive intelligence and robotic process automation capabilities of transactional, financial, and marketplace enabling systems.

[0143] [Diagram 36] Figure 36 illustrates the opportunity mining functionality of the system for transactional, financial, and marketplace purposes.

[0144] [Figure 37] Figure 37 illustrates the adaptive edge compute management and edge intelligence capabilities of the system for transactional, financial, and marketplace enabling.

[0145] [Figure 38] Figure 38 illustrates the protocol adaptation and adaptive data storage capabilities of a system enabling transactions, finance, and marketplaces.

[0146] [Figure 39] Figure 39 illustrates the robotic business analysis capabilities of systems that enable transactions, finance, and marketplaces.

[0147] [Diagram 40] Figure 40 shows a blockchain and smart contract platform 1 for a forward market for access rights to events.

[0148] [Diagram 41] Figure 41 shows the algorithm and dashboard of the Forward Market blockchain and smart contract platform for access to events.

[0149] [Diagram 42] Figure 42 shows a blockchain and smart contract platform 1 for forward market demand aggregation.

[0150] [Diagram 43] Figure 43 shows Algorithm 1 and the dashboard of a blockchain and smart contract platform for aggregating forward market demand.

[0151] [Diagram 44] Figure 44 depicts a blockchain and smart contract platform for crowdsourcing for innovation1.

[0152] [Diagram 45] Figure 45 shows the algorithm and dashboard of a blockchain and smart contract platform for crowdsourcing for innovation.

[0153] [Diagram 46] Figure 46 depicts a blockchain and smart contract platform for crowdsourcing for evidence.

[0154] [Figure 47] Figure 47 shows the algorithm and dashboard of the blockchain and smart contract platform for crowdsourcing for evidence.

[0155] [Figure 48]Figure 48 shows the components and interactions of an embodiment of a lending platform having a set of data integration microservices, including data collection and monitoring services for processing lending entities and transactions.

[0156] [Figure 49] FIG. 49 shows the components and interactions of one embodiment of a rental platform in which a suite of rental solutions is supported by a data integration set of data collection and monitoring services, adaptive intelligent systems, and data storage systems.

[0157] [Figure 50] FIG. 50 illustrates components and interactions of an embodiment of a lending platform having a set of data integration blockchain services, smart contract services, social network analysis services, crowdsourcing services, and Internet of Things data collection and monitoring services for collecting, monitoring, and processing information regarding entities involved in or related to lending transactions.

[0158] [Figure 51] FIG. 51 illustrates the Internet of Things and interactions of components of a lending platform having a sensor platform for monitoring at least one of a set of assets, a set of collateral, and a guarantee of a loan, bond, or debt transaction.

[0159] [Figure 52] FIG. 52 illustrates the components and interactions of a lending platform having a crowdsourcing system for collecting information related to entities involved in lending transactions.

[0160] [Figure 53] Figure 53 shows an example of a crowdsourcing workflow realized on a lending platform.

[0161] [Figure 54] FIG. 54 illustrates components and interactions of an embodiment of a lending platform having a smart contract system that automatically adjusts interest rates on loans based on information collected via at least one of an Internet of Things system, a crowdsourcing system, a set of social network analysis services, and a set of data collection and monitoring services.

[0162] [Figure 55] FIG. 55 illustrates components and interactions of an embodiment of a lending platform having smart contracts that automatically restructure debt based on monitored conditions.

[0163] [Figure 56] Figure 56 shows the components and interactions of a lending platform with a set of data collection and monitoring systems to verify the authenticity of loan guarantees, including an Internet of Things system and a social network analysis system.

[0164] [Figure 57] Figure 57 shows the components and interactions of a lending platform with a robotic process automation system for negotiating the terms of a loan.

[0165] [Figure 58] Figure 58 shows the components and interactions of a lending platform with a robotic process automation system for loan collection.

[0166] [Figure 59] Figure 59 shows the components and interactions of a lending platform with a robotic process automation system for orchestrating a series of loans.

[0167] [Figure 60] FIG. 60 illustrates the components and interactions of a lending platform with a robotic process automation system for managing factored loans.

[0168] [Figure 61] Figure 61 shows the components and interactions of a lending platform with a robotic process automation system for brokering mortgage loans.

[0169] [Figure 62] FIG. 62 illustrates the components and interactions of a lending platform having a crowdsourcing and automated classification system for verifying bond issuer terms, a social network monitoring system with artificial intelligence for classifying terms related to the bonds, and an Internet of Things data collection and monitoring system with artificial intelligence for classifying terms related to the bonds.

[0170] [Figure 63] Figure 63 shows the components and interactions of a lending platform having a system for managing loan terms based on parameters monitored by the IoT, parameters determined by a social network analysis system, or parameters determined by a crowdsourcing system.

[0171] [Figure 64] Figure 64 illustrates the components and interactions of a lending platform with an automated blockchain custody service for managing a set of custodial assets.

[0172] [Figure 65]Figure 65 shows the components and interactions of a lending platform having an underwriting system for loans with a set of data integration microservices including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for underwriting loan entities and transactions.

[0173] [Figure 66] Figure 66 shows the components and interactions of a lending platform with a loan marketing system with a set of data integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for marketing loans to a set of prospective buyers.

[0174] [Figure 67] Figure 67 illustrates the components and interactions of a lending platform having a rating system with a set of data-integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for rating a set of loan-related entities.

[0175] [Figure 68] FIG. 68 illustrates components and interactions of a lending platform having a regulatory and / or compliance system with a set of data integration microservices, including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services, to automatically facilitate compliance with at least one of laws, regulations, and policies applicable to lending transactions.

[0176] [Figure 69] FIG. 69 shows a system for automated loan management.

[0177] [Figure 70] Figure 70 shows an example of the system.

[0178] [Figure 71] Figure 71 shows how loans are handled.

[0179] [Figure 72] Figure 72 shows a system for adaptive intelligence and robotic process automation capabilities that enable transactions, finance, and marketplaces.

[0180] [Figure 73] Figure 73 shows how to automate the creation of smart contracts and allocation of collateral.

[0181] [Figure 74] FIG. 74 shows a system for processing loans.

[0182] [Figure 75] Figure 75 shows how loans are handled.

[0183] [Figure 76] Figure 76 illustrates a system for adaptive intelligence and robotic process automation.

[0184] [Figure 77] Figure 77 shows how loans are created and managed.

[0185] [Figure 78] Figure 78 shows a system for adaptive intelligence and robotic process automation capabilities that enable transactions, finance, and marketplaces.

[0186] [Figure 79]Figure 79 shows a method for Robotic Process Automation of trading, financial and market activities.

[0187] [Figure 80] Figure 80 illustrates a system for adaptive intelligence and robotic process automation.

[0188] [Figure 81] FIG. 81 shows a method for automating trading, financial and market activities.

[0189] [Figure 82] Figure 82 shows a system for adaptive intelligence and robotic processes.

[0190] [Figure 83] FIG. 83 illustrates a method for performing actions related to a loan.

[0191] [Figure 84] Figure 84 shows a system for adaptive intelligence and robotic processes.

[0192] [Figure 85] FIG. 85 illustrates a method for performing actions related to a loan.

[0193] [Figure 86] Figure 86 shows a system for adaptive intelligence and robotic processes.

[0194] [Figure 87] FIG. 87 illustrates a method for performing actions related to a loan.

[0195] [Figure 88] Figure 88 shows a smart contract system for managing loan collateral.

[0196] [Figure 89] Figure 89 shows a smart contract method for managing loan collateral.

[0197] [Figure 90] Figure 90 shows a system for verifying the collateral and guarantor conditions of a loan.

[0198] [Figure 91] Figure 91 shows how crowdsourcing can be used to verify collateral and guarantor conditions.

[0199] [Figure 92] FIG. 92 illustrates a smart contract system for modifying a loan.

[0200] [Figure 93] Figure 93 shows a smart contract method for modifying a loan.

[0201] [Figure 94] FIG. 94 illustrates a smart contract system for modifying a loan.

[0202] [Figure 95] Figure 95 shows a smart contract method for modifying a loan.

[0203] [Figure 96] FIG. 96 illustrates a smart contract system for modifying a loan.

[0204] [Figure 97] Figure 97 shows a smart contract method for modifying a loan.

[0205] [Figure 98] FIG. 98 illustrates a monitoring system for verifying the terms of a loan guarantee.

[0206] [Figure 99] Figure 99 shows the monitoring method for verifying the loan guarantee conditions.

[0207] [Figure 100] FIG. 100 illustrates a robotic process automation system for negotiating a loan.

[0208] [Figure 101] Figure 101 illustrates a Robotic Process Automation method for negotiating a loan.

[0209] [Figure 102] Figure 102 shows a system for adaptive intelligence and robotic process automation.

[0210] [Figure 103] FIG. 103 illustrates a method for the system of FIG.

[0211] [Figure 104] Figure 104 shows a system for adaptive intelligence and robotic process automation.

[0212] [Figure 105] FIG. 105 illustrates a method for the system of FIG.

[0213] [Figure 106] Figure 106 shows a system for adaptive intelligence and robotic process automation.

[0214] [Figure 107] FIG. 107 illustrates a method for the system of FIG.

[0215] [Figure 108]Figure 108 shows a system for adaptive intelligence and robotic process automation.

[0216] [Fig. 109] FIG. 109 illustrates a method for the system of FIG.

[0217] [Figure 110] Figure 110 shows a system for adaptive intelligence and robotic process automation.

[0218] [Figure 111] FIG. 111 illustrates a method for the system of FIG.

[0219] [Figure 112] Figure 112 shows a system for adaptive intelligence and robotic process automation.

[0220] [Figure 113] FIG. 113 illustrates a method for the system of FIG.

[0221] [Fig. 114] Figure 114 shows a system for adaptive intelligence and robotic process automation.

[0222] [Figure 115] FIG. 115 illustrates a method for the system of FIG.

[0223] [Fig. 116] FIG. 116 shows a system for monitoring the status of bond issuers.

[0224] [Figure 117] FIG. 117 illustrates a method for monitoring the status of a bond issuer.

[0225] [Fig. 118] FIG. 118 shows a system for monitoring the status of bond issuers.

[0226] [Figure 119] FIG. 119 illustrates a method for monitoring the status of a bond issuer.

[0227] [Figure 120] FIG. 120 shows an example of the system.

[0228] [Figure 121] FIG. 121 illustrates a method for the system of FIG.

[0229] [Fig. 122] FIG. 122 shows an example of the system.

[0230] [Figure 123] FIG. 123 illustrates a method for collecting social network information about entities involved in a subsidized loan transaction.

[0231] [Figure 124] FIG. 124 shows an example of the system.

[0232] [Fig. 125] FIG. 125 illustrates a method for automating the handling of subsidized loans.

[0233] [Fig. 126] FIG. 126 shows an example of the system.

[0234] [Figure 127] FIG. 127 is an example of the system of FIG.

[0235] [Figure 128] FIG. 128 shows an example of the system.

[0236] [Figure 129] Figure 129 shows a method for facilitating the attachment of security. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0237] The term service / microservice (and similar terms) as used herein should be understood broadly. Without being limited to other aspects or descriptions of the present disclosure, a service / microservice includes any system (or platform) configured to functionally perform the operations of a service, where the system may be data integrated, including data collection circuitry, blockchain circuitry, artificial intelligence circuitry, and / or smart contract circuitry for processing lending entities and transactions. A service / microservice may facilitate data handling and may include facilities for data extraction, transformation and loading, facilities for data cleansing and deduplication, facilities for data normalization, facilities for data synchronization, facilities for data security, facilities for computation (e.g., facilities for performing predefined computational operations on data streams and providing output streams), facilities for compression and decompression, facilities for analysis (such as providing automated generation of data visualizations), facilities for data processing, and / or facilities for data storage (including storage retention, formatting, compression, migration, etc.), etc.

[0238] A service / microservice may include controllers, processors, network infrastructure, input / output devices, servers, client devices (e.g., laptops, terminals, mobile devices, and / or dedicated devices), sensors (e.g., IoT sensors associated with one or more entities, equipment, and / or collateral), actuators (e.g., auto-locks, notification devices, lights, camera controls, etc.), virtualized versions of any one or more of the foregoing (e.g., outsourced computing resources such as cloud storage, computing operations, virtual sensors, collected subscribed data such as stock or commodity prices, record logs, etc.), and / or components configured as computer-readable instructions that, when executed by a processor, cause the processor to perform one or more functions of the service. A service may be distributed across multiple devices and / or the functions of the service may be performed by one or more devices that cooperate to perform the given functions of the service.

[0239] A service / microservice may include application programming interfaces that facilitate connectivity between components of a system (e.g., microservices) that execute the service, and between the system and entities external to the system (e.g., programs, websites, user devices, etc.). Without being limited to other aspects of the disclosure, exemplary microservices that may be present in certain embodiments include: (a) a multimodal set of data collection circuitry that collects and monitors information about entities related to loan transactions; (b) a blockchain circuitry for maintaining a secure historical ledger of loan-related events, the blockchain circuitry having access control functionality that governs access by a set of parties involved in the loan; c) a set of application programming interfaces, data integration services, data processing workflows, and user interfaces for processing loan-related events and loan-related activities; and (d) a smart contract circuitry for specifying the terms of a smart contract that governs at least one of the loan terms, loan-related events, and loan-related activities. Any of the services / microservices may be controlled by or have control over the controller. Certain systems may not be considered services / microservices. For example, a point-of-sale device that simply charges a set cost for goods or services may not be a service. In another example, a service that tracks the cost of goods or services and issues notifications when the value changes may not be the rating service itself, but may depend on the rating service and may form part of the rating service in certain embodiments.It will be appreciated that a given circuit, controller, or device may be a service or part of a service in certain embodiments, such as when the functionality or capabilities of the circuit, controller, or device are configured to support a service or microservice described herein, but may not be a service or part of a service in other embodiments (e.g., when the functionality or capabilities of the circuit, controller, or device are not related to a service or microservice described herein). In another example, a mobile device operated by a user may form part of a service described herein at a first time (e.g., when the user accesses functionality of the service via an application or other communication from the mobile device and / or when a monitoring function is being performed via the mobile device), but may not form part of the service at a second time (e.g., after a transaction is completed, after the user uninstalls the application, and / or when the monitoring function is stopped and / or handed over to another device). Thus, the benefits of the present disclosure may be applied to a wide variety of processes or systems, any such process or system may be considered a service (or part of a service) herein.

[0240] One of ordinary skill in the art, given the benefit of the disclosure herein and knowledge of contemplated systems typically available to that person, can readily determine which aspects of the disclosure will benefit a particular system and how the processes and systems of the disclosure can be combined and constructed to provide performance characteristics (e.g., bandwidth, computational power, time response, etc.) and / or operational capabilities (e.g., uptime requirements including time between checks, longitudinal (e.g., continuous operation time) and / or sequential (e.g., time of day, calendar time, etc.), sensing resolution and / or accuracy, data determination (e.g., accuracy, timing, data volume), and / or actuator confirmation capabilities) of components of a service sufficient to provide a given embodiment of the services, platforms, and / or microservices described herein. Specific considerations that one of ordinary skill in the art should take into account when determining the configuration of components, circuits, controllers, and / or devices for implementing the services, platforms, and / or microservices described herein (in the list below, "Services") include, but are not limited to, the following: the balance of capital costs versus operational costs in implementing and operating the service; the availability, speed, and / or bandwidth of network services available to system components, service users, and / or other entities that interact with the service; response times when considering a service (e.g., how quickly decisions within the service must be made to support the commercial functionality of the service, the operation times of various artificial intelligence and other advanced computational processes), and / or the capital or operational costs to support a given response time; the location of interacting components of the service, and the impact of such location on the operation of the service (e.g., location of data storage, relevant regulatory schemes, and / or the impact of such location on the operation of the service).The locations of components that interact with the service and the impact such location has on the operation of the service (e.g., location of data storage and associated regulatory schemes, limitations and costs of network communications, power costs depending on location, whether or not the service supports time zones relevant to the service, etc.); the availability of certain types of sensors and associated support for those sensors, and the availability of sufficient substitutes (e.g., cameras may require lighting support); the underlying value aspects of the service (e.g., loan principal, value of collateral, changes in value of collateral, net worth or relative net worth of the lender, guarantor, borrower, etc.), including the time sensitivity of the underlying values ​​(e.g., loan principal, value of collateral, changes in value of collateral, net worth or relative net worth of the lender, guarantor, borrower, etc.); trust metrics between the parties to the transaction (performance history between the parties, credit ratings, social ratings, or other external metrics relevant to the transaction); (e.g., conformance of the activity to an industry standard or other standardized transaction type), and / or availability of cost recovery options (e.g., subscription, fee, payment for services, etc.) for a given configuration and / or functionality of the service, platform, and / or microservice. Without being limited to other aspects of this disclosure, certain operations performed by the services herein include executing real-time changes to loans based on the tracked data, utilizing the data to execute secured smart contracts, revaluing debt transactions depending on the tracked state or data, etc. While specific examples of services / microservices and considerations are described herein for illustrative purposes, any system having the benefit of the disclosure herein and any considerations that would be understood by one of ordinary skill in the art having the benefit of the disclosure herein are specifically contemplated within the scope of this disclosure.

[0241] Services include, but are not limited to, financial services (e.g., loan transaction services), data collection services (e.g., data collection services for collecting and monitoring data), blockchain services (e.g., blockchain services for maintaining secure data), data integration services (e.g., data integration services for aggregating data), smart contract services (e.g., smart contract services for determining aspects of a smart contract), software services (e.g., software services for extracting data related to entities from publicly available information sites), crowdsourcing services (e.g., crowdsourcing services for soliciting and reporting information), Internet of Things services (e.g., Internet of Things services for monitoring the environment), publishing services (e.g., publishing services for publishing data), and the like. services), microservices (e.g., having a set of application programming interfaces that facilitate connectivity between microservices), valuation services (e.g., using valuation models to set values ​​for collateral based on information), artificial intelligence services, market value data collection services (e.g., monitoring and reporting market information), clustering services (e.g., grouping collateral items based on similarity of attributes), social networking services (e.g., social networking services (e.g., services that allow configuration regarding parameters of a social network), asset identification services (e.g., services for identifying a set of assets for which a financial institution is responsible), identity management services (e.g., services for a financial institution to verify identities and credentials), etc., and / or using similar functional terms.Examples of services performing one or more functions herein include computing devices; servers; network devices; user interfaces; device-to-device interfaces such as communication protocols, shared information and / or information storage, and / or application programming interfaces (APIs); sensors (e.g., IoT sensors operatively coupled to monitored components, equipment, locations, etc.); distributed ledgers; circuits; and / or computer readable code configured to cause a processor to perform one or more functions of the service. One or more aspects or components of the services herein may be distributed across multiple devices and / or may be aggregated in whole or in part to a given device. In embodiments, aspects or components of the services herein may be implemented at least in part through circuits, such as, by way of non-limiting examples, a data collection service implemented at least in part as a data collection circuit structured to collect and monitor data, a blockchain service implemented at least in part as a blockchain circuit structured to maintain secure data, a data integration service implemented at least in part as a data integration circuit structured to aggregate data, a smart contract service implemented at least in part as a smart contract circuit structured to determine aspects of the smart contract. a software service implemented at least in part as a software service circuit that extracts data relating to an entity from a publicly available information site; a crowdsourcing service implemented at least in part as a crowdsourcing circuit that solicits and reports information; an Internet of Things service implemented at least in part as an Internet of Things circuit that monitors the environment; a publishing service implemented at least in part as a publishing service circuit that publishes data; and a microservice service implemented at least in part as a microservice circuit that interconnects a plurality of service circuits.a valuation service implemented at least in part as a valuation service circuit for accessing a valuation model for setting a value for a collateral property based on the data, an artificial intelligence service implemented at least in part as an artificial intelligence service circuit, a market value data collection service implemented at least in part as a market value data collection service circuit for monitoring and reporting market information, a clustering service implemented at least in part as a clustering service circuit for grouping collateral properties based on attribute similarities, a social networking service implemented at least in part as a social networking analytics service circuit for setting parameters for a social network, an asset identification service implemented at least in part as an asset identification service circuit for identifying a set of assets for which a financial institution has custody responsibility, an identity management service implemented at least in part as an identity management service circuit for a financial institution to verify identities and credentials, etc. Thus, the benefits of the present disclosure may be applied to a wide variety of systems, and such systems may be considered with respect to the items and services herein, while in certain embodiments, a given system may not be considered with respect to the items and services herein. One of ordinary skill in the art, with the benefit of the disclosure herein and knowledge of the contemplated systems typically available to him or her, can readily determine which aspects of the disclosure will benefit a particular system and / or how to combine processes and systems of the disclosure to enhance the operation of a contemplated system. Among the considerations one of ordinary skill in the art may have in determining the configuration for a particular service include: distribution and access devices available to one or more parties to a particular transaction, jurisdictional restrictions on the storage, type, and communication of particular types of information, requirements or desirable aspects regarding security and validation of information communications of the service, information collection, inter-party communications, and response times of decisions made by the algorithms, machine learning components, and / or artificial intelligence components of the service.Considerations regarding the cost of the Services, including capital and operating costs, which party or entity will bear the costs, whether costs can be recovered through subscription or service fees or otherwise, the amount of information stored and / or communicated in support of the Services, and / or the processing or computing power utilized to support the Services.

[0242] The terms items and services (and similar terms) as used herein should be understood broadly. Without being limited to other aspects or explanations of the present disclosure, items and services include items and services used as compensation, items and services used as collateral, items and services that are the subject of negotiation, and the like, such as products, services, deliverables, solutions, physical products, software, service levels, service quality, financial instruments, debt, secured items, performance of services, other items, applications for guarantees on items that are the subject of financing, collateral for financing, and the like. Without being limited to other aspects or descriptions of the present disclosure, the items and services may include items and services applied to physical items (e.g., vehicles, ships, airplanes, buildings, homes, real estate properties, undeveloped land, farms, crops, municipal facilities, warehouses, sets of inventory, antiques, fixtures, items of furniture, items of equipment, tools, items of machinery, and items of personal possessions), financial items (e.g., goods, securities, currency, tokens of value, tickets, cryptocurrencies), consumables (e.g., edible items, beverages), high-value items (e.g., precious metals, items of jewelry, gemstones), intellectual items (e.g., items of intellectual property, intellectual property rights, contractual rights), and the like. Thus, the benefits of the present disclosure may be applied to a wide variety of systems, any such system may be considered with respect to the items and services herein, while in certain embodiments, a given system may not be considered with respect to the items and services herein. One of ordinary skill in the art, with the benefit of the disclosure herein and knowledge of the contemplated systems typically available to him or her, will be able to readily determine which aspects of the present disclosure will benefit a particular system and / or how to combine the processes and systems of the present disclosure to enhance the operation of the contemplated system.

[0243] Agent, automated agent, and similar terms as used herein should be understood broadly. Without being limited to other aspects or descriptions of the present disclosure, an agent or automated agent can process events related to at least one of the value, status, and ownership of an item of collateral or assets. Also, the agent or automated agent can take actions related to loans, debt transactions, bond transactions, subsidized loans, etc., to which the collateral or assets are subject, such as in response to the processed events. The agent or automated agent can interact with the marketplace for purposes of collecting data, testing spot market transactions, executing transactions, etc., where the operation of a dynamic system includes complex interactions that a user may wish to understand, predict, control, and / or optimize. A particular system may not be considered an agent or automated agent. For example, if events are merely collected but not processed, the system may not be an agent or automated agent. In some embodiments, if a loan-related action is taken that is not in response to a processed event, it may not have been taken by an agent or automated agent. One of ordinary skill in the art, having the benefit of the disclosure herein and knowledge of the contemplated systems typically available to that person, can readily determine which aspects of the disclosure include and / or benefit from an agent or automated agent. Particular considerations for embodiments of the disclosure involving an agent or automated agent include, but are not limited to, rules for determining when there has been a change in the value, condition or ownership of an asset or collateral, and / or rules for determining whether a change warrants further action on a loan or other transaction, and other considerations. While specific examples of market values ​​and market information are described herein for illustrative purposes, any embodiment having the benefit of the disclosure herein, and any considerations understood by one of ordinary skill in the art having the benefit of the disclosure herein, are specifically contemplated within the scope of the disclosure.

[0244] Market information, market value, and similar terms as utilized herein should be understood broadly. Without being limited to other aspects or explanations of this disclosure, market information and market value describe the condition or value of an asset, collateral, food, or service at a defined point in time or period. Market value may refer to the expectations placed on an item in a market or auction setting, or pricing or financial data for an item, asset, or collateral-like item in at least one public market. For a business, market value is the number of shares outstanding multiplied by the current stock price. Valuation services may include market value data collection services that monitor and report market information related to the value (e.g., market value) of a collateral, an issuer, a set of bonds, a set of assets, a set of subsidized loans, parties, etc. Market value may be dynamic in nature, as it depends on a variety of factors ranging from physical operating conditions to economic conditions to the dynamics of supply and demand. Market value may be affected by, and market information may include, proximity to other assets, inventory or supply of the asset, demand for the asset, origin of the item, history of the item, current value of the underlying components of the item, bankruptcy status of the company, foreclosure status of the company, default status of the company, regulatory violation status of the company, criminal status of the company, export control status of the company, embargo status of the company, etc., the export control status of the entity, the embargo status of the entity, the tariff status of the entity, the tax payment status of the entity, the credit report of the entity, the credit rating of the entity, the website rating of the entity, a set of customer reviews for the entity's products, the social network rating of the entity, a set of qualifications of the entity, a set of referrals of the entity, a set of testimonials of the entity, a set of actions of the entity, the location of the entity, and the geographic location information of the entity. In certain embodiments, market value may include information such as the volatility of value, the sensitivity of value (e.g., relative to other parameters having an uncertainty associated therewith), and / or the particular value of the valued object to a particular party (e.g., the object may be more valuable if owned by a first party than if owned by a second party).

[0245] Some information may not be market information or market value. For example, if a value-related variable is not market derived, it may be a use value or an investment value. In certain embodiments, the investment value may be considered a market value (e.g., if the appraiser intends to use the asset as an investment if acquired) and in other embodiments may not be considered a market value (e.g., if the appraiser intends to immediately liquidate the investment if acquired). A person skilled in the art, having the benefit of the disclosure herein and knowledge of the contemplated system typically available to him / her, can easily determine which aspects of the present disclosure benefit from market information or market value. For a person skilled in the art, certain considerations in determining whether the term market value refers to an asset, item, collateral, goods, or services include the presence of other similar assets in the market, changes in value by location, opening bids for an item exceeding list price, and other considerations. Specific examples of market value and market information are described herein for illustrative purposes, but any embodiment having the benefit of the disclosure herein and any considerations understood by a person skilled in the art having the benefit of the disclosure herein are specifically contemplated within the scope of the present disclosure.

[0246] The term apportionment value or apportionment value and similar terms utilized herein should be understood broadly. Without being limited to other aspects or explanations of the present disclosure, apportionment value describes the process of distributing or allocating value proportionately, or dividing and allocating value according to the rules of pro rata distribution. The allocation of value may be to multiple parties (e.g., multiple parties each being the beneficiary of a portion of the value), to multiple transactions (e.g., each transaction utilizing a portion of the value), and / or in a many-to-many relationship (e.g., a group of objects has an aggregate value that is allocated among multiple parties and / or transactions). In some embodiments, the value may be a net loss, and the allocated value is an allocation of liabilities to each entity. In other embodiments, the allocated value may refer to the distribution or allocation of economic benefits, real estate, collateral, and the like. For example, if a $10 million asset is allocated 50 / 50 between two parties, one party may take credit for the allocation if the parties consider different values ​​for the asset, resulting in a different value as a result of the allocation. For example, a first type of transaction (e.g., a long-term loan) may have a different valuation of assets than a second type of transaction (e.g., a short-term line of credit).

[0247] Certain conditions or processes may not be relevant to the allocated value. For example, the total value of an item may provide its inherent value, but not how much value each identified entity holds. Those skilled in the art, having the benefit of the disclosure herein and knowledgeable about allocated value, can readily determine which aspects of the present disclosure would benefit a particular application for allocated value. Specific considerations for those skilled in the art, or for embodiments of the present disclosure regarding allocated value, include, but are not limited to, the currency of the principal, the type of transaction anticipated (loan, bond, or debt), the type of specific collateral, the ratio of loan to value, the ratio of collateral to loan, the total transaction / loan amount, the amount of the principal, the number of entities owed the debt, the value of the collateral, etc. While specific examples of allocated values ​​are described herein for illustrative purposes, any embodiment having the benefit of the disclosure herein, and any considerations understood by those skilled in the art having the benefit of the disclosure herein, are specifically contemplated within the scope of the present disclosure.

[0248] The term financial condition and similar terms used herein should be understood broadly. Without being limited to any other aspect or description of this disclosure, financial condition refers to the current state of the company's assets, liabilities, and capital position at a defined point in time or period. Financial condition may be recorded in financial statements. Financial condition may also include an assessment of the company's ability to weather future risk scenarios and meet future or maturing obligations. Financial condition may be based on a set of attributes selected from the following: a public valuation of the company, a set of assets owned by the company as shown by public documents, a valuation of a set of assets owned by the company, a bankruptcy status of the company, a foreclosure status of the company, a contract default status of the company, a regulatory violation status of the company, a criminal status of the company, an export control status of the company, an embargo status of the company, and a set of attributes owned by the company. The entity's regulatory violation status, the entity's criminal status, the entity's export control status, the entity's embargo status, the entity's tariff status, the entity's tax status, the entity's credit report, the entity's credit rating, the entity's website rating, a set of customer reviews for the entity's products, the entity's social network rating, a set of the entity's credentials, a set of the entity's referrals, a set of the entity's testimonials, a set of the entity's actions, the entity's location, and the entity's geographic location. Financial status may also represent conditions or thresholds for contracts or loans. For example, a condition for a developer to proceed with development may be agreement to various certificates and financial payments. That is, the developer's ability to proceed with development is contingent on financial factors, among other things. Some conditions may not be financial conditions. For example, a credit card balance alone may provide a clue to the financial status, but may not be a financial status by itself. In another example, a payment schedule may determine how long a debt has been on a company's balance sheet, but may not provide an accurate financial status by itself. One of ordinary skill in the art, given the benefit of the disclosure herein and knowledge of the contemplated systems typically available to him or her, will be able to readily determine which aspects of the present disclosure involve and / or benefit from financial conditions.Matters that one of ordinary skill in the art would consider in determining whether the term financial condition refers to the current state of a company's asset, liability, and capital position at a defined point or period and / or for a given purpose include reporting of multiple financial data points, loan to collateral value ratios, loan to collateral ratios, total deal / loan amounts, borrower and lender credit scores, and other considerations. While specific examples of financial terms are set forth herein for illustrative purposes, any embodiment having the benefit of the disclosure herein, and any considerations that would be understood by one of ordinary skill in the art having the benefit of the disclosure herein, are specifically contemplated within the scope of the present disclosure.

[0249] The term interest rate and similar terms as used herein should be understood broadly. Without being limited to other aspects or explanations of the present disclosure, interest rate includes the amount of interest payable per period as a percentage of the amount lent, deposited, or borrowed. The total interest on an amount lent or borrowed may depend on the principal, the interest rate, the frequency of compounding, and the period of time for which it is lent, deposited, or borrowed. Typically, interest rates are expressed as a yearly percentage, but they may also be defined in any period. Interest rates relate to the amount that a lender, such as a bank, charges to borrow its money, or the rate that a bank or the like pays savers to keep their money in an account. Interest rates may be floating or fixed. For example, interest rates may vary depending on the instructions of a government or other stakeholder, the currency of the principal being lent or borrowed, the time to maturity of the investment, the perceived probability of default of the borrower, demand and supply in the market, the amount of collateral, the state of the economy, or special features such as call clauses. In certain embodiments, the interest rate may be a relative rate (e.g., a rate relative to the prime rate, an inflation index, etc.). In certain embodiments, the interest rate may further take into account costs or fees (e.g., "points") applied to adjust the interest rate. A nominal interest rate may not adjust for inflation, whereas a real interest rate takes inflation into account. A particular example may not be an interest rate for purposes of a particular embodiment. For example, a bank account growing by a fixed dollar amount each year and / or growing by a fixed fee amount may not be an example of an interest rate for a particular embodiment. A person skilled in the art with the benefit of the disclosure herein and knowledge of interest rates can easily determine the characteristics of an interest rate for a particular embodiment. Specific considerations for a person skilled in the art of interest rates, or for an embodiment of the present disclosure, include, but are not limited to, the following: the currency of the principal, the variables for setting the interest rate, the basis for modifying the interest rate, the type of transaction (loan, bond, or debt) expected, the type of specific collateral, the ratio of loan to value, the ratio of collateral to loan, the total transaction / loan amount, the amount of the principal, the appropriate life of the transaction and / or collateral in a particular industry, the likelihood that the lender will sell and / or consolidate the loan before the term, and the like.Although particular examples of interest rates are set forth herein for illustrative purposes, any embodiment having the benefit of the disclosure herein, and any considerations that would be understood by a person of ordinary skill in the art having the benefit of the disclosure herein, is specifically contemplated within the scope of the disclosure.

[0250] The term valuation service (and similar terms) as utilized herein should be understood broadly. Without being limited to other aspects or descriptions of the present disclosure, a valuation service includes any service that sets a value on an item or service. The valuation service may use a valuation model to set a value for collateral based on information from a data collection and monitoring service. A smart contract service may process the output from a series of valuation services to allocate items of collateral sufficient to provide security for a loan and / or allocate the value of items of collateral among a series of lenders and / or transactions. The valuation service may include an artificial intelligence service that iteratively improves the valuation model based on outcome data related to transactions of collateral. The valuation service may include a market value data collection service that monitors and reports market information related to the value of the collateral. Certain processes may not be considered valuation services. For example, a point-of-sale device that simply charges a set cost for goods or services may not be a valuation service. In another example, a service that tracks the cost of goods or services and provides notifications when the value changes may not be a valuation service itself, but may depend on and / or form part of a valuation service. Thus, the benefits of the present disclosure may be applicable to a wide variety of process systems, and any such process or system may be considered an assessment service herein, while in certain embodiments, certain services may not be considered assessment services herein. One of ordinary skill in the art, with the benefit of the disclosure herein and knowledge of the contemplated systems typically available to him or her, can readily determine which aspects of the present disclosure would benefit a particular system and how processes and systems from the present disclosure may be combined to enhance the operation of the contemplated systems and / or provide assessment services.Particular considerations that one of skill in the art would take in determining whether a contemplated system is a valuation service and / or whether aspects of the present disclosure would benefit a contemplated system include, but are not limited to, making real-time changes to loans based on the value of collateral, utilizing market data to execute collateral-backed smart contracts, revaluing collateral based on state of custody or geographic location, collateral having volatile value, prone to being utilized and / or moved, etc. While particular examples of valuation services and considerations are described herein for illustrative purposes, any system having the benefit of the disclosures herein, and any considerations that would be understood by one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.

[0251] The term collateral attributes (and similar terms) as utilized herein should be understood broadly. Without being limited to other aspects or descriptions of this disclosure, collateral attributes include identifications such as durability (the ability of the collateral to withstand wear and tear, or the useful life of the collateral), value, identifiability (whether the collateral has distinct characteristics that make it easy to identify or market), stability of value (whether the collateral maintains its value over time), standardization, grade, quality, marketability, liquidity, transferability, desirability, traceability, deliverability (can the collateral be delivered or transferred without depreciation), market transparency (whether the value of the collateral is easily verifiable or widely agreed upon), physical or virtual. Collateral attributes can be measured absolutely or relatively and can include qualitative (e.g., categorical descriptions) or quantitative descriptions. Collateral attributes may vary across different industries, products, elements, uses, etc. Collateral attributes can be assigned quantitative or qualitative values. Values ​​associated with collateral attributes may be based on a scale (e.g., 1-10) or a relative designation (e.g., high, low, good, etc.). Collateral includes various components, and each component may have collateral attributes. Thus, a collateral may have multiple values ​​for the same collateral attribute. In some embodiments, multiple values ​​of a collateral attribute may be combined to generate a single value for each attribute. Some collateral attributes may only apply to certain parts of the collateral. Some collateral attributes may have different values, even for certain components of the collateral, depending on the stakeholders (e.g., a party that values ​​certain aspects of the collateral more highly than other parties) and / or depending on the type of transaction (e.g., a collateral may be more valuable or appropriate for a first type of loan than a second type of loan). A particular attribute associated with a collateral may not be a collateral attribute as described herein, depending on the purpose of the collateral attributes herein.For example, a product may be rated as durable relative to similar products, but if the product's lifespan is much shorter than the term of the particular loan under consideration, the product's durability may be rated differently (e.g., not durable) or irrelevant (e.g., if the current inventory of the product is attached as collateral and is expected to be replaced during the term of the loan). Thus, the benefits of the present disclosure may be applied to a variety of attributes, any such attributes may be considered collateral attributes herein, while in certain embodiments, certain attributes may not be considered collateral attributes herein. One of ordinary skill in the art, with the benefit of the disclosure herein and knowledge of contemplated collateral attributes typically available to that person, can readily determine which aspects of the present disclosure benefit a particular collateral attribute. Specific considerations that one of skill in the art may use to determine whether a contemplated attribute is a collateral attribute and / or whether aspects of the present disclosure would benefit a contemplated system include, but are not limited to, the source of the attribute and the source of the attribute value (e.g., whether the attribute and attribute value come from a trusted source), the volatility of the attribute (e.g., whether the attribute value of the collateral fluctuates, whether the attribute is a new attribute of the collateral), the relative differences in the attribute values ​​of similar collateral, exceptional values ​​of the attribute (e.g., some attribute values ​​may be high, such as the 98th percentile, and some attribute values ​​may be very low, such as the 2nd percentile, compared to similar classes of collateral), fungibility of the collateral, the type of transaction associated with the collateral, and / or the purpose for utilizing the collateral for a particular party or transaction. While particular examples of collateral attributes and considerations are described herein for illustrative purposes, any system having the benefit of the disclosures herein, and any considerations that would be understood by one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.

[0252] The term blockchain service (and similar terms) as utilized herein should be understood broadly. Without being limited to other aspects or descriptions of the present disclosure, blockchain services include any services related to processing, recording, and / or updating a blockchain, and may include services for processing blocks, computing hash values, generating new blocks in a blockchain, adding blocks to a blockchain, creating forks in a blockchain, merging forks in a blockchain, verifying previous calculations, updating a shared ledger. Creating forks in a blockchain, merging forks in a blockchain, verifying previous calculations, updating a shared ledger, updating a distributed ledger, generating cryptographic keys, validating transactions, maintaining a blockchain, updating a blockchain, validating a blockchain, generating random numbers. Services may be performed by execution of computer-readable instructions on a local computer and / or by remote servers and computers. A particular service may not be considered a blockchain service individually, but may be considered a blockchain service based on the ultimate use of the service and / or in a particular embodiment. For example, computing a hash value may be performed in a context outside of a blockchain, such as in the context of a secure communication. Some initial services may be invoked without first being applied to a blockchain, but further actions or services that interface with the initial service may associate the initial service with aspects of a blockchain. For example, random numbers may be periodically generated and stored in memory. The random numbers may be utilized by the blockchain without initially being generated for the blockchain purpose. Thus, the benefits of the present disclosure may be applied in a wide variety of services, any of which may be considered a blockchain service herein, while in certain embodiments, a given service may not be considered a blockchain service herein.A person skilled in the art, having the benefit of the disclosure herein and knowledge of contemplated blockchain services typically available to that person, can readily determine which aspects of the present disclosure can be configured to implement and / or benefit from a particular blockchain service. Specific considerations in determining whether a contemplated service is a blockchain service and / or whether aspects of the present disclosure can benefit or enhance a contemplated system include, but are not limited to, the use of the service, the source of the service (e.g., if the service is associated with a known or verifiable blockchain service provider), the responsiveness of the service (e.g., some blockchain services may have an expected completion time and / or may be determined by usage), the cost of the service, the amount of data required for the service, and / or the amount of data generated by the service (blocks of a blockchain or keys associated with a blockchain may be of a particular size or a particular range of sizes). While specific examples of blockchain services and considerations are described herein for illustrative purposes, any system benefiting from the disclosure herein, and any considerations understood by a person skilled in the art having the benefit of the disclosure herein, are specifically contemplated within the scope of the present disclosure.

[0253] The term blockchain (and variations such as cryptocurrency ledger) as utilized herein is understood broadly to describe a cryptocurrency ledger that records, manages, or otherwise processes online transactions. A blockchain may be, without limitation, public, private, or a combination thereof. A blockchain may also be used to represent a set of digital transactions, agreements, terms, or other digital value. In the former case, and without being limited to other aspects or descriptions of the present disclosure, a blockchain may also be used in connection with investment applications, token trading applications, and / or digital / cryptocurrency-based marketplaces. A blockchain may also be associated with the provision of consideration, such as the provision of goods, services, items, fees, access to restricted areas or events, data, or other valuable benefits. Various forms of blockchain may be included when discussing units of consideration, collateral, currency, cryptocurrency, or other forms of value. One of ordinary skill in the art with the benefit of the disclosure herein and commonly available knowledge of the contemplated system can readily determine the value symbolized or represented by a blockchain. Although particular examples of blockchains are described herein for purposes of illustration, any embodiment having the benefit of the disclosure herein, and any considerations that would be understood by a person of ordinary skill in the art having the benefit of the disclosure herein, is specifically contemplated within the scope of this disclosure.

[0254] The terms ledger and distributed ledger (and similar terms) as used herein should be understood broadly. Without being limited to other aspects or descriptions of this disclosure, a ledger may be a document, file, computer file, database, book, etc. that maintains a record of transactions. A ledger may be physical or digital. A ledger may include records related to sales, accounts, purchases, transactions, assets, liabilities, income, expenses, capital, etc. A ledger may provide a history of transactions associated with time. A ledger may be centralized or distributed. A centralized ledger may be a document that is managed, updated, or viewable by one or more selected entities or clearinghouses, and changes or updates to the ledger may be managed or controlled by the entities or clearinghouses. A distributed ledger is a ledger that is distributed to multiple entities, participants, or regions, which may update or amend their copies of the ledger independently, simultaneously, or with consent. A ledger or distributed ledger may include security measures and cryptographic features for signing, concealing, and verifying content. In the case of a distributed ledger, blockchain technology may be used. In the case of a distributed ledger implemented using blockchain, the ledger may be a Merkle tree consisting of a linked list of nodes where each node contains the hashed or encrypted transaction data of the previous node. A particular transaction record may not be considered a ledger. A file, computer file, database, or book may or may not be a ledger depending on what data it stores and how the data is organized, maintained, or secured. For example, a list of transactions is not considered a ledger if it cannot be trusted or verified, or if it is based on inconsistent, fraudulent, or incomplete data. Ledger data may be organized in any format, such as a table, list, or binary stream of data, depending on convenience, source of data, type of data, environment, application, etc.A ledger shared among various entities may not be a distributed ledger, although the distinction of distributed may be based on which entities have the authority to make changes to the ledger and / or how changes are shared and processed among the different entities. Thus, the benefits of the present disclosure may be applicable to a wide variety of data, any such data may be considered a ledger herein, while in certain embodiments, certain data may not be considered a ledger herein. A person skilled in the art, with the benefit of the disclosure herein and knowledge of contemplated ledgers and distributed ledgers generally available to him / her, can readily determine which aspects of the present disclosure may be utilized to implement and / or benefit a particular ledger. Specific considerations for a person skilled in the art in determining whether a contemplated data is a ledger and / or whether aspects of the present disclosure may benefit or enhance a contemplated ledger include, but are not limited to, the following: security of the data in the ledger (can the data be tampered with or modified?), the time it takes to modify the data in the ledger, the cost (computationally and financially) of the modification, the details of the data, and the configuration of the data (does the data need to be processed for use in an application?). Data confidentiality (who can see or track data on the ledger), infrastructure size, communication requirements (distributed ledgers may require communication interfaces and specific infrastructure), resilience. While specific examples of blockchain services and considerations are described herein for illustrative purposes, any system having the benefit of the disclosure herein, and any considerations understood by one of ordinary skill in the art having the benefit of the disclosure herein, are specifically contemplated within the scope of this disclosure.

[0255] The term loan (and similar terms) as used herein should be understood broadly. Without being limited to other aspects or explanations of this disclosure, a loan may be a contract involving a borrowed asset that is expected to be returned in kind (e.g., borrow money and return money) or as an agreed upon transaction (e.g., a first good or service is borrowed and money, a second good or service, or a combination thereof is returned). An asset may be money, property, time, a physical object, a virtual object, a service, a right (e.g., a ticket, license, or other right), a depreciation charge, a credit (e.g., tax credit, emission credit, etc.), an agreed assumption of risk or liability, and combinations thereof. A loan is based on a formal or informal contract between a borrower and a lender, where the lender may provide an asset to the borrower for a predefined period, a variable period, or an indefinite period. The lender and the borrower may be individuals, entities, corporations, governments, groups of people, organizations, etc. Types of loans include mortgages, personal loans, secured loans, unsecured loans, concession loans, commercial loans, and microloans. A contract between the borrower and the lender may specify the terms of the loan. The borrower may be required to return an asset or to repay with a different asset than the one borrowed. In some cases, interest may be required to be repaid on the borrowed asset. The borrower and the lender may be intermediaries between other entities and may not own or use the asset. In some embodiments, the loan may not involve a direct transfer of an item, but rather a right of use or a shared right of use. In certain embodiments, the contract between the borrower and the lender may be executed between the borrower and the lender and / or may be executed with an intermediary (e.g., the beneficiary of the loan interest, such as through a sale of the loan). In certain embodiments, the contract between the borrower and lender may be executed via the services herein, such as via a smart contract service that determines at least a portion of the terms of the loan, and in certain embodiments, may commit the borrower and / or lender to the terms of the contract, which may be a smart contract.In certain embodiments, the smart contract service may input the terms of the agreement and present it to the borrower and / or lender for execution. In certain embodiments, the smart contract service may automatically commit one of the borrower or lender to the terms (at least as an offer) and present the offer to the other of the borrower or lender for execution. In certain embodiments, a loan agreement may include multiple borrowers and / or multiple lenders, such as when a set of loans includes multiple payment beneficiaries and / or when a set of loans includes multiple borrowers. In certain embodiments, the risks and / or obligations of a set of loans may be individualized (e.g., each borrower and / or lender is associated with a particular loan of the set of loans), allocated (e.g., a default on a particular loan has an associated loss allocated among the lenders), and / or a combination thereof (e.g., one or more subsets of the set of loans may be treated separately and / or allocated).

[0256] Certain contracts may not be considered loans. Contracts to transfer or borrow assets may not be loans depending on what assets are transferred, how the assets are transferred, or the parties involved. For example, in some cases, the transfer of assets may be for an indefinite period and be considered a sale or permanent transfer of the assets. Similarly, in some cases, if the assets are borrowed or transferred without clear terms or no consensus was reached between the lender and borrower, it may not be considered a loan. Even if a formal agreement is not directly codified in a contract, as long as the parties willingly and knowingly consent to the arrangement and / or the usual practice (e.g., in a particular industry), the transaction may be treated as a loan. Thus, the benefit of the present disclosure may be applied in a wide variety of contracts, any such contract may be considered a loan herein, while in certain embodiments, a given contract may not be considered a loan herein. A person skilled in the art, having the benefit of the disclosure herein and knowledge of the assumed loans that are typically available to him or her, can easily determine which aspects of the present disclosure may make a loan, take a loan, or benefit a particular loan transaction. Particular considerations that one of ordinary skill in the art would take in determining whether a contemplated loan is a loan and / or whether aspects of the present disclosure could benefit or enhance a contemplated loan include, but are not limited to, the value of the assets involved, the ability of the borrower to return or repay the loan, the type of assets involved (e.g., the amount of the loan ...

[0257] The term loan-related event (and similar terms including loan-related events) as utilized herein should be understood broadly. Without being limited to other aspects or explanations of the present disclosure, a loan-related event may include an event related to the terms of a loan or an event triggered by a contract related to a loan. A loan-related event may include a loan default, a contract breach, performance, repayment, payment, a change in interest, assessment of late fees, assessment of refunds, distribution, and the like. A loan-related event may be triggered by an explicit contract term. For example, a contract may specify that an interest rate will increase after a certain period of time has passed since the origination of a loan, and an increase in interest rate triggered by the contract may be a loan-related event. A loan-related event may be triggered implicitly by the relevant loan contract term. In certain embodiments, any occurrence that is considered to be related to the prerequisites of a loan contract and / or the expectations of the parties to the loan contract may be considered an occurrence of an event. For example, if the collateral for a loan is expected to be exchangeable (e.g., inventory as collateral), a change in inventory levels may be considered an occurrence of an event related to a loan. In another example, when a review and / or confirmation of the collateral is expected, lack of access to the collateral, disabled or failed monitoring sensors, etc. may be considered to be the occurrence of a loan-related event. In certain embodiments, the circuitry, controller, or other devices described herein may automatically trigger the determination of a loan-related event. In some embodiments, a loan-related event may be triggered by an entity managing the loan or loan-related agreement. A loan-related event may be conditionally triggered based on one or more conditions in the loan agreement. A loan-related event may be related to a task or requirement that a lender, borrower, or third party needs to complete. A particular event may be considered a loan-related event in certain embodiments and / or in certain contexts, but may not be considered a loan-related event in other embodiments or contexts.Many events may be caused by external triggers that are loan-related but not loan-related. However, in certain embodiments, an externally triggered event (e.g., a change in a commodity price related to a collateral item) may be a loan-related event. For example, a renegotiation of loan terms initiated by a lender may not be considered a loan-related event if the terms and / or performance of the existing loan agreement did not trigger the renegotiation. Thus, the benefits of the present disclosure may be applied to a wide variety of events, any of which may be considered a loan-related event herein, while in certain embodiments, a given event may not be considered a loan-related event herein. One of ordinary skill in the art, with the benefit of the disclosure herein and knowledge of the contemplated system typically available to that person, can readily determine which aspects of the present disclosure may be considered loan-related events for the contemplated system and / or a particular transaction supported by the system. Specific considerations in determining whether contemplated data is a loan-related event and / or whether aspects of the present disclosure may benefit or enhance a contemplated trading system include, but are not limited to, the impact of the relevant event on the loan (events that cause a loan default or termination may have a higher impact), the costs (capital and / or operational) associated with the event, the costs (capital and / or operational) associated with monitoring the occurrence of the event, the entity responsible for responding to the event, the time period and / or response time associated with the event (e.g., the time required to complete the event and the time allotted from when the event occurs until the event is desired to be processed or detected), the entity responsible for the event, the data required to process the event (e.g., sensitive information may have different safeguards or restrictions), the availability of mitigating measures in the event of an undetected event, and / or the remedies available to the party at risk in the event of an undetected event.Although specific examples of loan-related events and considerations are described herein for illustrative purposes, any system having the benefit of the disclosure herein, and any considerations that would be understood by a person of ordinary skill in the art having the benefit of the disclosure herein, are specifically contemplated within the scope of the present disclosure.

[0258] The term loan-related activities (and similar terms) as used herein should be understood broadly. Without being limited to other aspects or descriptions of this disclosure, loan-related activities may include activities related to the origination, maintenance, termination, collection, enforcement, servicing, billing, marketing, performance, or negotiation of a loan. Loan-related activities may include activities related to the signing of a loan agreement or promissory note, review of loan documents, processing of payments, valuation of collateral, evaluation of the borrower's or lender's compliance with the loan terms, renegotiation of terms, perfection of security or collateral for a loan, and / or negation of terms. Loan-related activities may relate to events related to a loan prior to the formal agreement of terms, such as activities related to initial negotiations. Loan-related activities may relate to events during the life of a loan and after the termination of a loan. Loan-related activities may be conducted by the lender, the borrower, or a third party. An activity may not be considered a loan-related activity individually, but may be considered a loan-related activity based on the specificity of the activity to the life cycle of the loan. For example, an invoice or invoice related to an outstanding loan may be considered loan-related activity, but if the invoice or invoice for the loan is combined with an invoice or invoice for an element that is not related to the loan, the invoice or invoice may not be considered loan-related activity. Some activities may be performed in connection with an asset regardless of whether a loan is related to the asset, in which case the activity would not be considered loan-related activity. For example, a periodic audit related to an asset may be performed regardless of whether the asset is related to a loan and may not be considered loan-related activity. In another example, a periodic audit related to an asset may be required by a loan agreement and would not normally occur without a connection to the loan, in which case the activity may be considered loan-related activity.In some embodiments, an activity may be considered a loan-related activity if it is an activity that would not otherwise occur if the loan were inactive or non-existent, but in some cases may still be considered a loan-related activity (e.g., if an audit would normally occur but the lender does not have the ability to perform or review the audit, the audit may be considered a loan-related activity even though it would otherwise have already occurred). Thus, the benefits of the present disclosure may be applied to a wide variety of events, any of which may be considered a loan-related event herein, while in certain embodiments, certain events may not be considered a loan-related event herein. A person skilled in the art, with the benefit of the disclosure herein and knowledge of the contemplated system generally available to that person, may readily determine loan-related activity for purposes of the contemplated system. Particular considerations for a person skilled in the art in determining whether contemplated data is loan-related activity and / or whether aspects of the present disclosure may benefit or enhance a contemplated loan include, but are not limited to, the following: The necessity of the activity to the loan (can the loan agreement or terms be satisfied without the activity), the cost of the activity, the uniqueness of the activity to the loan (is the activity similar or identical to other industries), the time the activity will take, the impact the activity will have on the life cycle of the loan, the entity performing the activity, the amount of data required for the activity (does the activity require confidential information related to the loan or personal information related to the entity), and / or the ability of the parties to perform and / or review the activity. While specific examples of events and considerations related to a loan are described herein for purposes of illustration, any system having the benefit of the disclosures herein, and any considerations that would be understood by one of ordinary skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of this disclosure.

[0259] Terms such as loan-terms, loan terms, terms for a loan, terms and conditions, etc., used herein ("loan-terms") should be understood broadly. Without being limited to other aspects or explanations of this disclosure, loan terms may relate to conditions, rules, restrictions, contractual obligations, etc. related to timing, repayment, origination, and other enforceable terms agreed upon by the borrower and the loan lender. Loan terms may be specified in a formal contract between the borrower and the lender. Loan terms may specify aspects such as interest rates, collateral, mortgage terms, debt consequences, payment methods, payment schedules, covenants, etc. Loan terms are negotiable and may change during the life of the loan. Loan terms may change or be affected by external parameters such as market prices, bond prices, lender or borrower related conditions, etc. Certain aspects of a loan may not be considered loan terms. In certain embodiments, aspects of a loan that are not formally agreed upon between the lender and borrower and / or that are not typically understood in the course of business (and / or in a particular industry) may not be considered a loan condition. Certain aspects of a loan may be preliminary or informal until formally agreed upon or confirmed in a contract or formal agreement. Certain aspects of a loan may not be considered a loan condition individually, but may not be considered a loan condition based on the specificity of the aspect to a particular loan. Certain aspects of a loan may not be considered a loan condition at a particular point in the loan, but may be considered a loan condition at another point in the loan (e.g., obligations and / or waivers that may arise due to the parties' performance and / or expiration of the loan term). For example, an interest rate may not be considered a loan condition generally until it is defined in the context of the loan, and compounded interest (annual interest, monthly interest), how it is calculated, etc. Certain aspects of a loan may not be considered a term if it is unclear or unenforceable. Some aspects indicate a condition of a loan. Some aspects may be related to a condition, but may not be a condition in themselves.For example, a term of a loan is the repayment period of the loan, such as one year. The term does not specify how the loan is repaid during the year. It may be repaid in 12 monthly payments or in one annual payment. The monthly payment plan in this case may not be considered the term of the loan, since it is merely one or many options for repayment that are not directly specified by the loan. Thus, the benefits of the present disclosure may be applied to a wide variety of aspects of a loan, any of which may be considered a loan term herein, while in certain embodiments, certain aspects may not be considered a loan term herein. A person skilled in the art, having the benefit of the disclosure herein and knowledge of the contemplated system typically available to him or her, can readily determine which aspects of the present disclosure are loan terms of the contemplated system.

[0260] Matters that a person skilled in the art should consider in determining whether the contemplated data is a loan term and / or whether aspects of the present disclosure could benefit or enhance the contemplated loan include, but are not limited to, the enforceability of the term (can the lender, lessor, or borrower enforce the term), the cost of enforcing the term (time or effort required to ensure the term is followed), the complexity of the term (how easily the parties can follow or understand the term, are the terms error-prone or susceptible to misinterpretation), the entity responsible for the term, the fairness of the term, the stability of the term (how often it changes), the observability of the term (can another party verify the term), the favorability of the term to one party (is the term favorable to the borrower or lessor), the risks associated with the loan (the term may depend on the likelihood that the loan will not be repaid), the characteristics of the borrower or lessor (their ability to meet the terms), and / or normal expectations for loans and the related industry.

[0261] Specific examples of loan terms are described herein for illustrative purposes only, but any considerations that would be understood by a system having the benefit of this disclosure, or that would be understood by a person of ordinary skill in the art having the benefit of this disclosure, are specifically contemplated within the scope of this disclosure.

[0262] As used herein, terms such as loan terms, loan conditions, terms of a loan, conditions, etc., should be understood broadly ("loan terms"). Without being limited to other aspects or explanations of this disclosure, loan terms may relate to rules, restrictions, and / or obligations related to a loan. Loan terms may relate to rules or necessary obligations for obtaining a loan, maintaining a loan, applying for a loan, transferring a loan, etc. Loan terms may include debt principal, debt balance, fixed interest rate, floating interest rate, payment amount, payment schedule, balloon payment schedule, collateral designation, collateral fungibility designation, collateral treatment, access to collateral, parties, guarantees, guarantors, collateral, personal guarantees, liens, terms, covenants, lien conditions, default conditions, conditions regarding the debtor's other debts, consequences of default, etc.

[0263] Certain aspects of a loan may not be considered loan conditions. Aspects of a loan that are not formally agreed upon between the lender and borrower and / or that are not commonly understood in the course of business (and / or in a particular industry) may not be considered loan conditions. Certain aspects of a loan may be preliminary or informal until formally agreed upon or confirmed in a contract or formal agreement. Certain aspects of a loan may not be considered loan conditions individually, but may be considered loan conditions based on the specificity of that aspect to a particular loan. Certain aspects of a loan may not be considered loan conditions at a particular time during a loan, but may be considered loan conditions at another time during a loan (e.g., obligations and / or waivers that may occur due to the parties' performance and / or expiration of a loan condition). Thus, the benefits of the present disclosure may be applicable in a wide variety of loan aspects, any of which may be considered loan conditions herein, while in certain embodiments, a given aspect may not be considered loan conditions herein. A person skilled in the art, having the benefit of the disclosure herein and knowledge of the contemplated system typically available to that person, can readily determine which aspects of the present disclosure are loan terms of the contemplated system. Specific considerations for a person skilled in the art in determining whether contemplated data are loan terms and / or whether aspects of the present disclosure can benefit or enhance the contemplated loan include, but are not limited to, the enforceability of the terms (can the lender, lessor or borrower enforce the terms), the cost of enforcing the terms (the time or effort required to ensure that the terms are followed), the complexity of the terms (how easily the parties can follow or understand the terms, are the terms prone to error or misinterpretation), who is responsible for the terms, the fairness of the terms, the observability of the terms (can other parties verify the terms), the favorability of the terms to one party (are the terms favorable to the borrower or the lender), the risks associated with the loan (the terms may depend on the likelihood that the loan will not be repaid), and / or the normal expectations for the loan and / or related industry.

[0264] Specific examples of loan terms are described herein for illustrative purposes only, but any considerations that would be understood by a system having the benefit of this disclosure, or that would be understood by a person of ordinary skill in the art having the benefit of this disclosure, are specifically contemplated within the scope of this disclosure.

[0265] The terms loan collateral, pledge, item of collateral, item of collateral, etc., used herein should be understood broadly. Without being limited to other aspects or explanations of the present disclosure, loan collateral may relate to any asset or property that a borrower pledges to a lender as a backup in exchange for a loan and / or as security for the loan. Collateral may be any item of value that is acceptable as an alternative means of repayment in the event of a loan default. Collateral may include any physical or virtual item or types of items, such as vehicles, boats, airplanes, buildings, homes, real estate, undeveloped land, farms, crops, municipal facilities, warehouses, lines of inventory, goods, securities, currency, tokens of value, tickets, cryptocurrencies, consumables, food products, beverages, precious metals, gemstones, intellectual property, intellectual property rights, contractual rights, antiques, fixtures, furniture, equipment, tools, machinery, personal property, etc.

[0266] A collateral item is an asset, property, value, or other item that is defined as collateral for a loan or transaction. A set of collateral items may be defined, and collateral items may be substituted, removed, or added within the set. For example, collateral items may be, but are not limited to, cars, boats, airplanes, buildings, homes, real estate, undeveloped land, farms, crops, municipal facilities, warehouses, inventory, merchandise, securities, currency, tokens of value, tickets, cryptocurrencies, consumables, food, beverages, precious metals, jewelry, gemstones, etc. Additionally, collateral items may include precious metals, jewelry, gemstones, intellectual property, intellectual property rights, contractual rights, antiques, fixtures, furniture, equipment, tools, machinery, personal property, etc. When a set or multiple collateral items are defined, the substitution, removal, or addition of a collateral item may be effectively performed as the substitution, removal, or addition of a collateral item to or from the set of collateral items. Without being limited to other aspects or descriptions of the present disclosure, a collateral item or set of collateral items may also be used in combination with other terms of the agreement or loan, such as representations, warranties, indemnities, covenants, debt balances, fixed interest rates, floating interest rates, payment amounts, payment schedules, balloon payment schedules, collateral designations, collateral fungibility designations, pledges, personal guarantees, liens, terms, lien conditions, default conditions, and default consequences. In certain embodiments, the smart contract may calculate whether the borrower has met a condition or covenant, and if the borrower has not met such a condition or covenant, may enable an automated action, trigger another condition or provision that may affect the status, ownership, or transfer of the collateral item, or initiate the replacement, removal, or addition of a collateral item to the collateral set of the loan. Those skilled in the art, having the benefit of the disclosure herein and knowledge of collateral items, may readily determine the purpose and use of the collateral items in the various embodiments and contexts disclosed herein, including their replacement, removal, and addition.

[0267] Although a specific example of loan collateral is described herein for purposes of illustration, any system having the benefit of the disclosure herein, and any considerations that would be understood by a person of ordinary skill in the art having the benefit of the disclosure herein, is specifically contemplated within the scope of this disclosure.

[0268] The term smart contract service (and similar terms) as utilized herein should be understood broadly. Without being limited to other aspects or descriptions of the present disclosure, a smart contract service includes any service or application that manages a smart contract or a smart lending contract. For example, a smart contract service may specify the terms of a mart contract, such as a rules database, or process the output from a set of evaluation services to allocate items of collateral sufficient to secure a loan. A smart contract service may automatically execute a set of rules or conditions that embody a smart contract, the execution of which may be based on or utilize collected data. A smart contract service may automatically initiate a loan payment request, automatically initiate a foreclosure process, automatically initiate an action to claim alternative or backup collateral, transfer ownership of collateral, automatically initiate an inspection process, automatically change the term of payments or interest on the collateral, or configure a smart contract to automatically perform an action related to a loan. A smart contract may specify at least one of loan terms, loan-related events, and loan-related activities. A smart contract may be an agreement encoded as a computer protocol that may facilitate, verify, or enforce the negotiation or performance of the smart contract. A smart contract may or may not be one or more of partially or fully self-executing, or partially or fully self-enforcing.

[0269] Certain processes may not be considered smart contract related individually, but may be considered smart contract related in an aggregated system. For example, automatically undertaking loan-related actions may not be smart contract related in one instance, but may be governed by the terms of a smart contract in another instance. Thus, the benefits of the present disclosure may be applicable to a wide variety of process systems, and any such process or system may be considered a smart contract or smart contract service herein, while in certain embodiments, a given service may not be considered a smart contract service herein.

[0270] Those skilled in the art, having the benefit of the disclosure herein and knowledge of the contemplated systems generally available to them, will be able to readily determine which aspects of the present disclosure benefit a particular system and how the processes and systems of the present disclosure may be combined to implement smart contract services and / or enhance the operation of the contemplated systems. Specific considerations that one of ordinary skill in the art may have in determining whether a contemplated system includes smart contract services or smart contracts and / or whether aspects of the present disclosure could benefit or enhance a contemplated system include, but are not limited to, the ability to automatically transfer ownership of collateral in response to an event; automated actions available when compliance (or lack of compliance) with covenants is found; collateral amenities for clustering, rebalancing, distribution, addition, substitution, and removal of items from collateral; modification parameters of aspects of a loan in response to an event (e.g., timing, complexity, suitability for loan type, etc.); the complexity of the system's terms of the loan, including benefits from quickly determining and / or predicting changes in entities related to the loan (e.g., collateral, financial status of the parties, collateral offsets, and industries related to the parties); the suitability of the automated generation and / or execution of terms for the type of loan, parties, and / or industry envisioned for the system; and the like. While particular examples of smart contract services and considerations are described herein for purposes of illustration, any system having the benefit of the disclosure herein, and any considerations that would be understood by a person of ordinary skill in the art having the benefit of the disclosure herein, are specifically contemplated within the scope of this disclosure.

[0271] The term IoT system (and similar terms) as utilized herein should be understood broadly. Without being limited to other aspects or descriptions of this disclosure, an IoT system includes any system of uniquely identified and interrelated computing devices, mechanical and digital machines, sensors, and objects that can transfer data over a network without intervention. Certain components may not be considered an IoT system individually, but may be considered an IoT system in an aggregated (e.g., single networked) system.

[0272] A sensor, a smart speaker, and / or a medical device may be part of a larger system without being an IoT system, and / or may be integrated with many other similar components to be considered an IoT system and / or part of an IoT system. In certain embodiments, a system may be considered an IoT system for some purposes but not others. For example, a smart speaker may be considered part of an IoT system for certain operations, such as providing surround sound, but not for other operations, such as streaming content directly from a single local network source. Furthermore, in certain embodiments, other similar looking systems may be differentiated in determining whether and / or what type of IoT system such a system is an IoT system. For example, one group of medical devices may not share into an aggregated HER database at a given time, while another group of medical devices may share data into an aggregated HER for clinical research purposes, and accordingly, one group of medical devices may be an IoT system, while the other group of medical devices may not. Thus, the benefits of the present disclosure may be applicable to a wide variety of systems, any of which may be considered an IoT system herein, while in certain embodiments, a given system may not be considered an IoT system herein. One of ordinary skill in the art, with the benefit of the disclosure herein and knowledge of the contemplated system typically available to him or her, will be able to readily determine which aspects of the present disclosure will benefit a particular system, how to combine processes and systems of the present disclosure to enhance the operation of the contemplated system, and what circuits, controllers, and / or devices comprise the IoT components of the contemplated system.Particular considerations for one of skill in the art in determining whether a contemplated system is an IoT system and / or whether aspects of the present disclosure can benefit or enhance the contemplated system include, but are not limited to, the transmission environment of the system (e.g., low power, availability of device-to-device networking), shared data storage for devices, establishment of geofences by devices, service as blockchain nodes, ability to monitor assets, collateral, or entities, relaying data between devices, ability to aggregate data from multiple sensors or monitoring devices, etc. Specific examples of IoT systems and considerations are described herein for illustrative purposes, however, any system having the benefit of the disclosure herein and any considerations as would be understood by one of skill in the art having the benefit of the disclosure herein are specifically contemplated within the scope of the present disclosure.

[0273] The term data collection service (and similar terms) as utilized herein should be understood broadly. Without being limited to other aspects or descriptions of the present disclosure, a data collection service includes any service that collects data or information, and includes any circuitry, controller, device, or application that can store, transmit, transfer, share, process, organize, compare, report, and / or aggregate data. A data collection service may include and / or communicate with a data collection device (e.g., a sensor). A data collection service may monitor an entity to collect data or information. A data collection service may be event-driven, run periodically, or obtain data from an application at a particular point during the execution of the application. A particular process may not be considered a data collection service individually, but may be considered a data collection service in an aggregated system. For example, a network-attached storage device may be a component of a data collection service in one example, but may have standalone functionality in another example. Thus, the benefits of the present disclosure may be applicable to a wide variety of process systems, and such processes or systems may be considered data collection services herein, while in certain embodiments, a given service may not be considered a data collection service herein. One of ordinary skill in the art, with the benefit of the disclosure herein and knowledge of the contemplated systems typically available to him or her, will be able to readily determine which aspects of the present disclosure will benefit a particular system and how processes and systems from the present disclosure can be combined to perform data collection services and / or enhance the operation of the contemplated systems.Particular considerations for one of skill in the art in determining whether a contemplated system is a data collection service and / or whether aspects of the present disclosure would benefit a contemplated system include, but are not limited to, the ability to change business rules on the fly to modify data collection protocols, performing real-time monitoring of events, connecting devices for data collection to a monitoring infrastructure, executing computer readable instructions that cause a processor to record or track events, using automated inspection systems, sales occurring at a networked point of sale, the need for data from one or more distributed sensors or cameras, etc. Specific examples of data collection services and considerations are described herein for illustrative purposes, however, any system having the benefit of the disclosure herein and any considerations that would be understood by one of skill in the art having the benefit of the disclosure herein are specifically contemplated within the scope of the present disclosure.

[0274] The term data integration service (and similar terms) as utilized herein should be understood broadly. Without being limited to other aspects or descriptions of the present disclosure, a data integration service includes any service that integrates data or information, including any device or application that can extract, transform, load, normalize, compress, decompress, encode, decode, and otherwise process data packets, signals, and other information. A data integration service may monitor entities, such as to identify data or information for integration. A data integration service may integrate data regardless of the required frequency, communication protocol, or business rules required for complex integration patterns. Thus, the benefits of the present disclosure may be applicable to a wide variety of process systems, and such processes or systems may be considered data integration services herein, while in certain embodiments, a given service may not be considered a data integration service herein. With the benefit of the disclosure herein and knowledge of the contemplated systems typically available to that person, one of ordinary skill in the art can readily determine which aspects of the present disclosure benefit a particular system and how the processes and systems of the present disclosure may be combined to implement data integration services and / or enhance the operation of the contemplated systems. Particular considerations for one of skill in the art in determining whether a contemplated system is a data integration service and / or whether aspects of the present disclosure would benefit a contemplated system include, but are not limited to, the ability to modify business rules on the fly to change data integration protocols, communication with third party databases to bring in data to be integrated, synchronization of data across different platforms, connection to a central data warehouse, data storage, processing, and / or communication capacity distributed across systems, connection of separate automated workflows, etc. Specific examples of data integration services and considerations are described herein for purposes of illustration, but any system having the benefit of the disclosure herein and any considerations as would be understood by one of skill in the art having the benefit of the disclosure herein are specifically contemplated within the scope of the present disclosure.

[0275] The term computational service (and similar terms) as utilized herein should be understood broadly. Without being limited to other aspects or descriptions of the present disclosure, a computational service may be included as part of one or more services, platforms, or microservices, such as blockchain services, data collection services, data integration services, evaluation services, smart contract services, data monitoring services, data mining, and / or any services that facilitate the collection, access, processing, transformation, analysis, storage, visualization, or sharing of data. A particular process may not be considered a computational service. For example, a process may not be considered a computational service depending on the type of rules governing the service, the end product of the service, or the intent of the service. Thus, the benefits of the present disclosure may be applicable to a wide variety of process systems, and such processes or systems may be considered computational services herein, while in certain embodiments, a given service may not be considered a computational service herein. A person skilled in the art, with the benefit of the disclosure herein and knowledge of the contemplated systems typically available to him or her, can readily determine which aspects of the present disclosure will benefit a particular system and how processes and systems from the present disclosure can be combined to perform one or more computational services and / or enhance the operation of the contemplated system. Particular considerations for a person skilled in the art in determining whether a contemplated system is a computational service and / or whether aspects of the present disclosure can benefit or enhance a contemplated system include, but are not limited to, the following: agreement-based access to services; brokering exchanges between different services; providing on-demand computational power for web services; achieving one or more of monitoring, collecting, accessing, processing, transforming, analyzing, storing, integrating, visualizing, mining, or sharing data.Although specific examples of computational services and considerations are described herein for purposes of illustration, any system having the benefit of the disclosure herein, and any considerations that would be understood by a person of ordinary skill in the art having the benefit of the disclosure herein, are specifically contemplated within the scope of this disclosure.

[0276] The term sensor as utilized herein should be understood broadly. Without being limited to other aspects or descriptions of the present disclosure, a sensor may be a device, module, machine, or subsystem that detects or measures a physical quality, event, or change. In embodiments, the detection or measurement may be recorded, displayed, transmitted, or otherwise responded to. Examples of sensors include sensors for detecting movement of an entity, sensors for detecting temperature, pressure, or other attributes related to the entity or its environment, cameras that capture still or video images of an entity, sensors that collect data related to collateral or assets, such as sensors that collect data related to location, condition (health, physical, or other), quality, security, ownership, etc. In embodiments, a sensor may be sensitive to a characteristic being measured but insensitive to other characteristics. A sensor may be analog or digital. A sensor may include a processor, a transmitter, a transceiver, a memory, power, detection circuitry, an electrochemical fluid reservoir, a light source, etc. Additionally, sensors may include biosensors, chemical sensors, black silicon sensors, infrared sensors, acoustic sensors, inductive sensors, motion sensors, optical sensors, opacity sensors, proximity sensors, inductive sensors, eddy current sensors, passive infrared proximity sensors, radar, capacitive sensors, capacitive displacement sensors, Hall effect sensors, magnetic sensors, GPS sensors, thermal imaging sensors, thermocouples, thermistors, photoelectric sensors, ultrasonic sensors, infrared laser sensors, inertial motion sensors, and the like.The sensors may include infrared laser sensors, inertial motion sensors, MEMS internal motion sensors, ultrasonic 3D motion sensors, accelerometers, inclinometers, force sensors, piezoelectric sensors, rotary encoders, linear encoders, ozone sensors, smoke sensors, heat sensors, magnetometers, carbon dioxide detectors, carbon monoxide detectors, oxygen sensors, glucose sensors, smoke detectors, metal detectors, rain sensors, altimeters, GPS, presence detection, context detection, activity detection, object detection (e.g., collateral), marker detection, and other capacitive, optical response, heart rate sensors, RF / micropower impulse radio (MIR) sensors. In some embodiments, the sensors may be virtual sensors, e.g., that computationally determine a parameter of interest based on other sensed parameters in the system. In certain embodiments, the sensors may be smart sensors - e.g., that report sensed values ​​as abstracted communications (e.g., as network communications). In certain embodiments, the sensors may provide sensed values ​​(e.g., as voltage levels, frequency parameters, etc.) directly to circuits, controllers, or other devices in the system. One of ordinary skill in the art, given the benefit of the disclosure herein and knowledge of the contemplated systems typically available to him or her, can readily determine which aspects of the disclosure would benefit from sensors. Considerations that one of ordinary skill in the art should consider when determining whether a contemplated device is a sensor and whether an aspect of the disclosure could benefit from or be enhanced by a contemplated sensor include, but are not limited to, tuning system start / stop to environmental quality, conversion of electrical output to measurements, ability to enforce geofencing, automatic loan modification in response to changes in collateral, etc. While specific examples and considerations of sensors are described herein for illustrative purposes, any system benefiting from the disclosure herein and any considerations that would be understood by one of ordinary skill in the art having the benefit of the disclosure herein are specifically contemplated within the scope of the present disclosure.

[0277] The term storage condition and similar terms utilized herein should be understood broadly. Without being limited to other aspects or descriptions of the present disclosure, storage condition includes the environment, physical location, environmental quality, exposure levels, security measures, maintenance descriptions, accessibility descriptions, etc. associated with the storage of an asset, collateral, or entity specified and monitored in a contract, loan, or agreement supporting the agreement. Based on the storage condition of the collateral, asset, or entity, actions may be taken to maintain, improve, and / or confirm the condition of the asset or the use of the asset as collateral. Based on the storage condition, steps may be taken to modify the terms of a loan or bond. Storage conditions may be classified according to various rules, thresholds, conditional procedures, workflows, model parameters, etc., and may be based on self-reporting, data from an Internet of Things device, data from a set of environmental condition sensors, data from a set of social network analysis services, a set of algorithms querying network domains, social media data, crowd-sourced data, etc. Storage conditions may be tied to a geographic location associated with the collateral, issuer, borrower, distribution of funds, or other geographic locations. Examples of IoT data may include images, sensor data, location data, etc. Examples of social media data and crowdsourced data include actions of parties to a loan, financial status of parties, and compliance of parties with terms and provisions of a loan or bond. Parties to a loan may include the bond issuer, related entities, lenders, borrowers, and third parties with an interest in the debt. Storage conditions may relate to assets and collateral types such as municipal property, vehicles, vessels, airplanes, buildings, homes, real estate properties, undeveloped land, farms, crops, municipal facilities, warehouses, sets of inventory, goods, securities, currency, tokens of value, tickets, cryptocurrencies, consumables, food products, beverages, precious metals, jewelry, intellectual property, intellectual property rights, contractual rights, antiques, fixtures, furniture, equipment, tools, machinery, and personal possessions. Storage conditions may also include environments selected from among a municipal environment, a corporate environment, a brokerage environment, a real estate environment, a commercial facility, a warehouse, a transportation environment, a manufacturing environment, a storage environment, a home, and a vehicle.Actions based on the custody status of a collateral, asset, or entity include managing, reporting, modifying, syndicating, consolidating, terminating, maintaining, modifying terms and / or conditions, seizing assets, or disposing of loans, contracts, or agreements. One of ordinary skill in the art, having the benefit of the disclosure herein and knowledge of the contemplated custody conditions, can readily determine which aspects of the present disclosure would benefit a particular application of custody conditions. Specific considerations that one of ordinary skill in the art, or an embodiment of the present disclosure, should consider when selecting appropriate custody conditions to manage and / or monitor include, but are not limited to, the legality of the terms given the jurisdiction of the transaction, the available data for a given collateral, the expected type of transaction (loan, bond or debt), the specific collateral type, the loan to value ratio, the collateral to loan ratio, the total transaction / loan amount, the borrower's and lender's credit scores, normal industry practices, and other considerations. Specific examples of custody conditions are described herein for illustrative purposes, but any embodiment having the benefit of the disclosure herein, and any considerations understood by one of ordinary skill in the art having the benefit of the disclosure herein, are specifically contemplated within the scope of the present disclosure.

[0278] The term geolocation and similar terms utilized herein are to be understood broadly. Without being limited to other aspects or descriptions of the present disclosure, geolocation includes the identification or estimation of a real-world geographic location of an object, including generating a set of geographic coordinates (e.g., latitude and longitude) and / or a street address. Based on the geolocation of a collateral, asset, or entity, action may be taken to maintain or improve the condition of the asset or the use of that asset as collateral. Based on the geolocation, action may be taken to modify the terms of a loan or bond. Based on the geolocation, decisions or predictions related to a transaction may be made based on, for example, weather, civil unrest in a particular area, and / or local disasters (e.g., earthquakes, floods, tornadoes, hurricanes, industrial accidents, etc.). Geolocation may be determined according to various rules, thresholds, conditional procedures, workflows, model parameters, etc., and may be based on self-reporting, data from Internet of Things devices, data from a set of environmental condition sensors, data from a set of social network analysis services, and a set of algorithms for querying network domains, social media data, crowd-sourced data, etc. Examples of geolocation data include GPS coordinates, images, sensor data, addresses, etc. Geolocation data may be quantitative (e.g., longitude / latitude, relative to a map, etc.) and / or qualitative (e.g., categories such as "coastal," "rural," etc., "in New York City," etc.). Geolocation data may be absolute (e.g., GPS location) or relative (e.g., within 100 yards of an expected location). Examples of social media or crowdsourced data may include actions of parties to a loan inferred by geolocation, financial status of parties inferred by geolocation, compliance of parties with terms or conditions of a loan or bond, etc. Geolocation may be determined for assets or collateral types such as municipal assets, vehicles, vessels, airplanes, buildings, homes, real estate properties, undeveloped land, farms, crops, municipal facilities, warehouses, inventory, merchandise, securities, etc.Additionally, currency, tokens of value, tickets, consumables, food, beverages, precious metals, jewelry, gemstones, antiques, fixtures, furniture, equipment, tools, machinery, personal possessions, and the like. Geolocation may be determined for an entity, such as one of the parties, a third party (e.g., an inspection service, maintenance service, cleaning service, etc., associated with the transaction), or other entity associated with the transaction. Geolocation may include an environment selected from among a municipal environment, a corporate environment, a securities trading environment, a real estate environment, a commercial facility, a warehouse facility, a transportation environment, a manufacturing environment, a storage environment, a home, and a vehicle. Actions based on the geographic location of the collateral, assets, or entity include managing, reporting, modifying, syndicating, consolidating, terminating, maintaining, modifying the terms and / or conditions, seizing assets, or otherwise disposing of loans, contracts, or agreements. Those skilled in the art with the benefit of the disclosure herein and knowledge of the contemplated system can readily determine which aspects of the present disclosure benefit a particular application for geolocation and which aspects of the location of an item are geolocations for the contemplated system. Specific considerations for one of ordinary skill in the art, or for embodiments of the present disclosure, in selecting an appropriate geolocation to manage include, but are not limited to, the legality of the geolocation given the jurisdiction of the transaction, available data for a given collateral, the expected type of transaction (loan, bond, or debt), the particular collateral type, loan to value ratio, collateral to loan ratio, total transaction / loan amount, considerations such as frequency of borrower travel to a particular jurisdiction, mobility of the collateral, and / or the likelihood of location-specific events occurring related to the transaction (e.g., weather, location of relevant industrial facilities, availability of related services, etc.). While specific examples of geolocations are described herein for illustrative purposes, any embodiment having the benefit of the disclosure herein, and any considerations understood by one of ordinary skill in the art having the benefit of the disclosure herein, are specifically contemplated within the scope of the present disclosure.

[0279] The term jurisdiction and similar terms utilized herein should be understood broadly. Without being limited to other aspects or descriptions of this disclosure, jurisdiction refers to the laws and legal authority governing the substance of a loan. Jurisdiction may be based on the geographic location of the entity, the place of registration of the entity (e.g., the flag state of a vessel, the state of incorporation of a company, etc.), the granting state of certain rights such as intellectual priority, etc. In certain embodiments, jurisdiction may be one or more of the geolocations of the entity in the system. In certain embodiments, jurisdiction may not be the same as the geolocation of the entity in the system (e.g., if the contract specifies other jurisdictions). In certain embodiments, jurisdiction may vary for different entities in the system (e.g., if the borrower is A, the lender is B, the collateral is placed at C, and the contract is enforced at D, etc.). In certain embodiments, jurisdiction for a given entity may change during operation of the system (e.g., due to movement of collateral, related data, changes in contract terms, etc.). In certain embodiments, a given entity of the system may have multiple jurisdictions (e.g., due to operation of relevant law and / or options available to one or more parties) and / or may have different jurisdictions for different purposes. The jurisdiction of a collateral, asset, or entity may determine certain terms of a loan or bond, by action, and / or may indicate different obligations with respect to notifying parties, foreclosure and / or execution of defaults, processing of collateral and / or debt security, and / or processing of various data within the system. While specific examples of jurisdictions are described herein for illustrative purposes, any embodiment having the benefit of the disclosure herein, and any considerations that would be understood by one of ordinary skill in the art having the benefit of the disclosure herein, are specifically contemplated within the scope of the present disclosure.

[0280] As utilized herein, the terms increment of value, token, and variations such as cryptocurrency token may be broadly understood to describe any of the following: a) units of currency or cryptocurrency (e.g., cryptocurrency tokens); and (b) credentials that can be exchanged for goods, services, data, or other valuable consideration (e.g., tokens of value). In the former case, tokens may also be used in conjunction with investment applications, token trading applications, and token-based marketplaces, without being limited to other aspects or descriptions of the present disclosure. In the latter case, tokens may also be associated with a provision of consideration, such as the provision of goods, services, fees, access to restricted areas or events, data, or other valuable benefits. Tokens may be contingent (e.g., contingent access tokens) or non-contingent. For example, a token of value may be exchanged for lodging (e.g., a hotel room), food / food products or services, space (e.g., shared space, workspace, convention space), fitness / wellness products or services, event tickets or event admission fees, transportation such as travel, airline tickets, digital content, virtual goods, license keys, or other goods, services, data, or consideration of value. Tokens in various forms may be included when discussing consideration, collateral, or units of value, whether currency, cryptocurrency, or other forms of value such as goods, services, data, or other benefits. Those of skill in the art with the benefit of the disclosure herein and knowledge of tokens can readily determine the value symbolized or represented by the token, whether currency, cryptocurrency, goods, services, data, or other value. While specific examples of tokens are described herein for illustrative purposes, any embodiment having the benefit of the disclosure herein, and any considerations understood by those of skill in the art having the benefit of the disclosure herein, are specifically contemplated within the scope of the present disclosure.

[0281] The term pricing data as used herein is broadly understood to represent a quantity of information, such as the price or cost of one or more items in a market. Without being limited to other aspects or descriptions of the present disclosure, pricing data may also be used in combination with spot market prices, forward market prices, price discount information, promotional prices, and other information related to the cost or price of an item. Pricing data may satisfy one or more conditions or trigger the application of one or more rules of a smart contract. Pricing data may be used in combination with other forms of data, such as market value data, accounting data, access data, asset / facility data, worker data, event data, underwriting data, claims data, etc. Pricing data may be tailored to the context of the item being valued (e.g., condition, liquidity, location, etc.) and / or the context of a particular party. Those of ordinary skill in the art with the benefit of the disclosure herein and knowledge of pricing data can readily determine the purpose and use of pricing data in the various embodiments and contexts disclosed herein.

[0282] Without being limited to other aspects or descriptions of the present disclosure, a token includes any token, such as a token of value, such as collateral, an asset, a reward, or the like, a token that serves as a representation of value, such as a value-bearing voucher that can be exchanged for goods or services. Certain components may not be considered tokens individually, but may be considered tokens in an aggregated system. For example, a value placed on an asset may not be a token itself, but the value of the asset may be placed on a token of value for storage, exchange, trading, etc. For example, in a non-limiting example, a blockchain circuit may be configured to provide lenders with a mechanism for storing the value of an asset, in which case the value attributed to the token is stored in the blockchain circuit's distributed ledger, but the token itself, with the value assigned to it, may be exchanged or traded, such as via a token marketplace. In certain embodiments, a token may be considered a token for some purposes but not for other purposes. For example, a token may be used as an indication of ownership of an asset, but the use of such a token is not traded, in which case a token containing the value of the asset may be traded as value. Thus, the benefits of the present disclosure may be applicable to a wide variety of systems, and such systems may be considered tokens herein, while in certain embodiments, a given system may not be considered a token herein. One of ordinary skill in the art, with the benefit of the disclosure herein and knowledge of the contemplated systems typically available to him or her, can readily determine which aspects of the present disclosure will benefit a particular system and / or how to combine processes and systems of the present disclosure to enhance the operation of the contemplated system.Particular considerations for those skilled in the art in determining whether a contemplated system is a token and / or whether aspects of the present disclosure can benefit or enhance a contemplated system include, but are not limited to, access data such as associated with access rights, tickets, and tokens, use in investment applications such as for investing in stocks, interests, and tokens, token trading applications, token-based marketplaces, forms of consideration such as monetary compensation and tokens, conversion of resource value in tokens, cryptocurrency tokens, conversion of resource value in tokens, etc., indications of ownership such as cryptocurrency tokens, identity information, event information, token information, etc., blockchain-based access tokens traded in marketplace applications, pricing applications such as pricing and monitoring of contingent access rights, underlying access rights, tokens, and fees, trading applications such as trading or exchanging contingent access rights or underlying access rights or tokens, tokens created and stored on the blockchain for contingent access rights that carry ownership rights (e.g., tickets), etc., hereinafter referred to as "tokens."

[0283] The term financial data as used herein is broadly understood to refer to a collection of financial information regarding assets, collateral, or other items. Financial data may include revenues, expenses, assets, liabilities, stocks, bond ratings, defaults, ROA (return on assets), ROI (return on investment), past performance, future expected performance, EPS (earnings per share), IRR (internal rate of return), earnings announcements, ratios, statistical analysis of the above (e.g., moving averages), and the like. Also, without being limited to other aspects or explanations of this disclosure, financial data may be used in combination with pricing data and market value data. The financial data may satisfy one or more conditions or trigger the application of one or more rules of a smart contract. The financial data may be used in combination with other forms of data, such as market value data, pricing data, accounting data, access data, asset and facility data, worker data, event data, underwriting data, claims data, or other forms of data. Those skilled in the art with the benefit of the disclosure herein and knowledge of financial data can readily determine the purpose and use of pricing data in the various embodiments and contexts disclosed herein.

[0284] The term covenant as used herein is broadly understood to denote a term, agreement or promise, such as the performance of some act or omission. For example, a covenant may relate to the actions of a party or the legal status of a party. Without being limited to other aspects or explanations of this disclosure, a covenant may also be used in combination with other terms related to a contract or loan, such as representation, warranty, indemnity, outstanding debt, fixed interest rate, floating interest rate, payment amount, payment schedule, balloon payment schedule, collateral designation, collateral fungibility designation, party, guarantee, guarantor, collateral, personal guarantee, lien, term, lien condition, default condition, and default consequence. A breach of a covenant or a commitment may satisfy one or more conditions or may trigger a recovery, breach or other condition. In certain embodiments, the smart contract may calculate whether a covenant is satisfied and may enable automated actions or trigger other conditions or clauses if the covenant is not satisfied. One of ordinary skill in the art, having the benefit of this disclosure and knowledge of covenants, can readily determine the purpose and use of the covenants in the various embodiments and contexts disclosed herein.

[0285] An entity, as used herein, is broadly understood to refer to an identifiable associate, such as a party, a third party (such as an auditor, regulator, service provider, etc.), and / or collateral property associated with a transaction. Examples of entities include individuals, partnerships, corporations, limited liability companies, and other legal organizations. Other exemplary entities include identifiable collateral items, offsetting collateral, potential collateral, etc. For example, an entity may be a given party, such as an individual, to a contract or loan. Data or other terms herein may be characterized as having a context related to the entity, such as entity-oriented data. An entity may be characterized by a particular context or application, such as, but not limited to, a human entity, a physical entity, a transaction entity, or a financial entity. An entity may have a representative acting on behalf of the entity. Without being limited to other aspects or descriptions of this disclosure, an entity may also be used in combination with other entities or terms related to a contract or loan, such as representations, warranties, indemnities, pledges, debt balances, fixed interest rates, variable interest rates, payment amounts, payment schedules, etc. The attributes of an entity may include, but are not limited to, a published valuation, a set of properties owned by the entity as shown by public records, a valuation of a set of properties owned by the entity, bankruptcy status, foreclosure status, contractual default status, regulatory violation status, criminal status, export control status, embargo status, and tariff status, as well as attributes such as, but not limited to, a credit report, a credit rating, a website rating, a set of customer reviews for the entity's products, a social network rating, a set of credentials, a set of referrals, a set of testimonials, a set of behaviors, location, and geolocation.In certain embodiments, the smart contract may calculate whether an entity meets conditions or covenants and activate automated actions or trigger other conditions or clauses if the entity does not meet such conditions or covenants. One of ordinary skill in the art with the benefit of the disclosure herein and knowledge of entities can readily determine the purpose and use of entities in the various embodiments and contexts disclosed herein.

[0286] The term party as utilized herein is understood broadly to refer to members of an agreement, such as individuals, partnerships, corporations, limited liability companies, or other legal entities. For example, a party may refer to a primary lender, a secondary lender, a loan syndicate, a corporate lender, a government lender, a bank lender, a secured lender, a bond issuer, a bond purchaser, an unsecured lender, a guarantor, a security provider, a borrower, a debtor, an underwriter, an inspector, an appraiser, an auditor, a valuation expert, a government official, an accountant, or any other entity having rights or obligations regarding a contract, transaction, or loan. A party may characterize different terms, such as a transaction, without limitation, such as the term multi-party transaction, in which multiple parties are involved in the transaction. A party may have a representative acting on its behalf. In certain embodiments, the term party may refer to a potential or prospective party, such as a willing lender or borrower interacting with the system, who may not yet be committed to an actual agreement during the interaction with the system. Also, without being limited to other aspects or descriptions of this disclosure, the parties may be used in combination with other parties and terms related to the contract or loan, such as representations, warranties, indemnities, covenants, outstanding debt, fixed interest rate, floating interest rate, payment amount, payment schedule, payment date, payment method, payment amount, payment schedule, balloon payment schedule, collateral designation, collateral fungibility designation, entity, guarantee, guarantor, collateral, personal guarantee, lien, term, lien conditions, default conditions, default consequences, etc. The parties may have a set of attributes, such as, without limitation, identity, creditworthiness, activities, conduct, business practices, contract performance status, information about accounts receivable, information about accounts payable, information about the value of collateral, and other types of information. In certain embodiments, the smart contract may calculate whether the parties have met the conditions or covenants and may activate automated actions or trigger other conditions or clauses if the parties have not met such conditions or covenants. Those skilled in the art with the benefit of the disclosure herein and knowledge of the parties can readily determine the purpose and use of the parties in the various embodiments and contexts disclosed herein.

[0287] The terms party attributes, entity attributes, or party / entity attributes as used herein are understood broadly to describe the value, characteristics, or state of a party or entity. For example, party or entity attributes may be, but are not limited to, value, quality, location, net worth, price, physical condition, health, security, safety, ownership, identity, creditworthiness, activity, behavior, business practices, contract performance, information regarding accounts receivable, information regarding accounts payable, information regarding the value of collateral, and other types of information. In certain embodiments, a smart contract may calculate values, states, or conditions associated with party or entity attributes and may enable automated actions or trigger other conditions or clauses if a party or entity does not meet such conditions or covenants. Those skilled in the art, having the benefit of the disclosure herein and knowledgeable regarding party or entity attributes, can readily determine the purpose and use of these attributes in the various embodiments and contexts disclosed herein.

[0288] The term "lender" as used herein is broadly understood to refer to a party to an agreement that provides assets for lending or loan proceeds, and includes an individual, partnership, corporation, limited liability company, or other legal entity. For example, but not limited to, a lender may be a primary lender, secondary lender, lending syndicate, corporate lender, government lender, bank lender, secured lender, unsecured lender, or any other party that has rights or obligations in an agreement, transaction, or loan that provides financing to a borrower. A lender may have an agent acting on its behalf. Without being limited to any other aspect or description of this disclosure, party may also be used in combination with other party or agreement or loan terms, such as borrower, guarantor, representation, warranty, indemnity, covenant, debt balance, fixed interest rate, floating interest rate, payment amount, etc. Fixed interest rates, floating interest rates, payment amounts, payment schedules, balloon payment schedules, collateral designations, collateral fungibility designations, collateral, personal guarantees, liens, terms, lien conditions, default conditions, default consequences, etc. In certain embodiments, the smart contract may calculate whether the lender has met the conditions or covenants and may enable automated actions, notifications or alerts, or trigger other conditions or clauses if the lender has not met such conditions or covenants. Those of ordinary skill in the art with the benefit of the disclosure herein and knowledge of lenders can readily determine the purpose and use of lenders in the various embodiments and contexts disclosed herein.

[0289] The term crowdsourcing service as utilized herein may broadly be understood as a service provided or rendered in connection with a crowdsourcing model or transaction. In a crowdsourcing model or transaction, a large group of people or entities provide contributions to fulfill a need, such as a loan. The crowdsourcing service may be provided by, without limitation, a platform or system. A crowdsourcing request may be communicated to a group of information providers, whereby responses to the request may be collected and processed to provide a reward to at least one successful information provider. The request and parameters may be configured to obtain information related to the status of a set of collateral for a loan. The crowdsourcing request may be made public. In certain embodiments, without limitation, the crowdsourcing service may be performed by a smart contract, and rewards are managed by a smart contract that processes responses to the crowdsourcing request and automatically assigns rewards to information that meets a set of parameters configured for the crowdsourcing request. Those skilled in the art, having the benefit of the disclosure herein and knowledge of crowdsourcing services, may readily determine the purpose and use of crowdsourcing services in the various embodiments and contexts disclosed herein.

[0290] The term publishing service as utilized herein may be understood to describe a set of services for publishing crowdsourcing requests. Publishing services may be provided by, without limitation, a platform or a system. In certain embodiments, without limitation, publishing services may be performed by a smart contract, where crowdsourcing requests are published or publishing is initiated by a smart contract. Those skilled in the art, having the benefit of the disclosure herein and knowledge of publishing services, can readily determine the purpose and use of publishing services in the various embodiments and contexts disclosed herein.

[0291] The term interface as used herein is understood broadly to refer to components that interact or communicate, such as computer components embodied in software, hardware, or a combination thereof. For example, an interface may be configured for a variety of purposes or for a variety of applications or contexts, such as, but not limited to, an application programming interface, a graphic user interface, a user interface, a software interface, a marketplace interface, a demand aggregation interface, a crowdsourcing interface, a secure access control interface, a network interface, a data integration interface, a cloud computing interface, or a combination thereof. An interface may function as a method for inputting, receiving, or displaying data, including, but not limited to, within the scope of lending, refinancing, collecting, consolidating, factoring, brokering, or foreclosure. An interface may function as an interface for another interface. Without being limited to other aspects or descriptions of this disclosure, an interface may be used in combination with or as part of an application, process, module, service, layer, device, component, machine, product, subsystem, interface, connection, or system. In some embodiments, the interface is embodied in software, hardware, or a combination thereof and stored on a medium or memory. One of ordinary skill in the art, having the benefit of this disclosure and knowledge of the interfaces, can readily determine the purpose and use of the interfaces in the various embodiments and contexts disclosed herein.

[0292] The term graphical user interface as used herein can be understood as a type of interface that allows a user to interact with a system, computer, or other interface, where the interaction or communication is accomplished by a graphical device or representation. A graphical user interface may be a component of a computer and may be embodied in computer readable instructions, hardware, or a combination thereof. A graphical user interface can serve many different purposes and can be configured for different applications or contexts. Such an interface can function as, but is not limited to, a method of receiving or displaying data using visual representations, stimuli, or interactive data. A graphical user interface may function as an interface for another graphical user interface or other interface. Without being limited to other aspects or descriptions of this disclosure, a graphical user interface can be used in combination with an application, process, module, service, layer, device, component, machine, product, subsystem, interface, connection, or as part of a system. In certain embodiments, a graphical user interface may be embodied in computer readable instructions, hardware, or a combination thereof and stored on a medium or memory. A graphical user interface may be configured to accommodate any input type, such as a keyboard, mouse, touch screen, etc. The graphical user interface may be configured for any desired user interaction environment including, for example, a dedicated application, a web page interface, or a combination thereof.One of ordinary skill in the art, having the benefit of this disclosure and knowledgeable about graphical user interfaces, will be able to readily determine the purpose and use of graphical user interfaces in the various embodiments and contexts disclosed herein.

[0293] A user interface, as used herein, is an interface through which a user interacts with a system, computer, or other device, and can be understood to involve interaction or communication through graphical devices or representations. A user interface may be a component of a computer, embodied in software, hardware, or a combination thereof. A user interface may be stored on a medium or memory. A user interface may include drop-down menus, tables, forms, and the like, with default, templated, recommended, or pre-set conditions. In some embodiments, a user interface may include voice interaction. Without being limited to other aspects or descriptions of this disclosure, a user interface may be used in combination with or as part of a system, an application, circuit, controller, process, module, service, layer, device, component, machine, product, subsystem, interface, connection. A user interface may serve many different purposes and be configured for different applications and contexts. For example, a lender user interface may include the ability to display multiple customer profiles, but may be limited in making certain changes. A borrower user interface may include the ability to view and change user account details. Third party neutral interfaces (e.g., regulators, auditors, etc., third parties with no stake in the underlying transaction) may have the ability to monitor the company and view anonymized user data without the ability to manipulate the data, and may have scheduled access depending on the third party and the purpose of the access. Third party stakeholder interfaces (e.g., collectors, debtor advocates, investigators, partial owners, etc., third parties that may have a stake in the underlying transaction) may include the ability to view certain user data, with restrictions on making changes.Many additional features of these user interfaces are available in the system and / or procedural embodiments described throughout this disclosure. Thus, the benefits of the present disclosure may be applied to a wide variety of processes and systems, and such processes or systems may be considered services herein. Those skilled in the art, with the benefit of the disclosure herein and knowledgeable about user interfaces, can readily determine the purpose and use of user interfaces in the various embodiments and contexts disclosed herein. Particular considerations for those skilled in the art in determining whether a contemplated interface is a user interface and / or whether aspects of the present disclosure can benefit or enhance a contemplated system include, but are not limited to, configurable views, the ability to limit operations or views, reporting capabilities, the ability to manipulate user profiles and data, implementing regulatory requirements, providing desired user functionality for borrowers, lenders, and third parties, and the like.

[0294] Interfaces and dashboards as used herein are understood broadly to describe components that facilitate interaction or communication, such as computer components embodied in software, hardware, or a combination thereof. The interfaces and dashboards may obtain, receive, present, or otherwise manage items, services, offerings, or other aspects of a transaction or loan. For example, an interface or dashboard may serve many different purposes or be configured for different applications or contexts, such as an application programming interface, a graphic user interface, a user interface, a software interface, a marketplace interface, a demand aggregation interface, a crowdsourcing interface, a secure access control interface, a network interface, a data integration interface, a cloud computing interface, or a combination thereof. An interface or dashboard may function as a way to receive or display data in, but not limited to, the context of lending, refinancing, collection, consolidation, factoring, brokering, or foreclosure. An interface or dashboard may function as an interface or dashboard for another interface or dashboard. Without being limited to other aspects or descriptions of the present disclosure, an interface may be used in combination with or as part of a system, an application, a circuit, a controller, a process, a module, a service, a layer, a device, a component, a machine, a product, a subsystem, an interface, a connection, etc. In certain embodiments, an interface or dashboard may be embodied in computer readable instructions, hardware, or a combination thereof, as well as stored on a medium or memory.One of ordinary skill in the art, having the benefit of this disclosure and generally available knowledge of the contemplated systems, will be able to readily determine the purpose and use of the interfaces and / or dashboards in the various embodiments and contexts disclosed herein.

[0295] The term domain as used herein is understood broadly to describe the scope or context of a transaction and / or communication related to a transaction. For example, a domain may serve many different purposes or be configured for different applications or contexts, such as, but not limited to, a domain for execution, a domain for digital assets, a domain where requests are published, a domain where social network data collection and monitoring services are applied, a domain where Internet of Things data collection and monitoring services are applied, a network domain, a geolocation domain, a jurisdictional location domain, and a time domain. Without being limited to other aspects or descriptions of the present disclosure, one or more domains may be utilized in connection with or as part of any application, circuit, controller, process, module, service, layer, device, component, machine, product, subsystem, interface, connection. A domain may be embodied in computer readable instructions, hardware, or a combination thereof, stored on a medium or memory. Those skilled in the art, having the benefit of the disclosure herein and knowledgeable about domains, may readily determine the purpose and use of a domain in the various embodiments and contexts disclosed herein.

[0296] The term "request" (and variations thereof) as used herein is understood broadly to refer to an act or instance of initiating or requesting the provision of something (information, a response, an object, etc.). A particular type of request may serve many different purposes or be configured for different applications or contexts. For example, but not limited to, a formal legal request (such as a subpoena), a refinancing request (such as a loan), or a crowdsourcing request. The system may be utilized to execute the request or to fulfill the request. When discussing legal actions, loan refinancing, or crowdsourcing services, various forms of requests may be included without limitation. Those skilled in the art having the benefit of the disclosure herein and knowledge of the contemplated system can readily determine the value of a request implemented in an embodiment. Although specific examples of requests are described herein for illustrative purposes, any embodiment having the benefit of the disclosure herein, and any considerations understood by those skilled in the art having the benefit of the disclosure herein, are specifically contemplated within the scope of the present disclosure.

[0297] The term reward (and variations thereof) as used herein is understood broadly to refer to something or something received or provided in response to an action or incentive. Rewards may be monetary or non-monetary, without limitation. A particular type of reward may serve many different purposes or be configured for different applications or contexts, such as, without limitation, reward events, reward claims, monetary rewards, rewards captured as datasets, reward points, or other forms of rewards. Rewards may be triggered, assigned, generated for innovation, provided for submission of evidence, requested, provided, selected, managed, administered, configured, assigned, communicated, and identified, as well as other actions, without limitation. To perform the aforementioned actions, the system may be utilized. Various forms of rewards may be included in discussing or encouraging a particular action, including, without limitation, the following: In certain embodiments herein, rewards may be utilized as specific incentives (e.g., rewarding specific people who respond to a crowdsourcing request) or as general incentives (e.g., providing rewards in response to successful crowdsourcing requests in addition to or instead of rewarding specific people who respond). Those of ordinary skill in the art having the benefit of the disclosure herein and knowledgeable about compensation can readily determine the value of the compensation implemented in the embodiments. Although specific examples of compensation are described herein for purposes of illustration, any embodiment having the benefit of the disclosure herein, and any considerations that would be understood by one of ordinary skill in the art having the benefit of the disclosure herein, is specifically contemplated within the scope of the present disclosure.

[0298] The term robotic process automation system as utilized herein may be broadly understood to describe a system capable of performing the tasks or providing the needs of the disclosed system. For example, a robotic process automation system may be configured for, but is not limited to, negotiating loan terms, negotiating loan refinancing, collecting loans, consolidating a series of loans, managing factoring loans, mediating mortgage loans, training for foreclosure negotiation, configuring crowdsourcing requests based on a set of loan attributes, setting rewards, determining a set of domains to which the request will be published, configuring the content of the request, configuring data collection and monitoring actions based on a set of loan attributes, determining a set of domains to which the Internet of Things data collection and monitoring services will be applied, and iteratively training and improving based on a set of results. A robotic process automation system may include a set of data collection and monitoring services, an artificial intelligence system, and another robotic process automation system that is a component of a higher-level robotic process automation system. A robotic process automation system may include: At least one of the set of mortgage activities and set of mortgage interactions includes activities among marketing activities, identifying potential borrowers, identifying property, identifying collateral, qualifying borrowers, title search, title verification, property appraisal, property inspection, property evaluation, income verification, borrower demographic analysis, identifying capital providers, determining available interest rates, determining available payment terms, determining available interest rates, analyzing existing mortgages, comparative analysis of existing mortgages and new mortgage terms, completing application workflow, entering application items, preparing mortgage agreements, completing mortgage agreement schedules, negotiating mortgage terms with capital providers, negotiating mortgage terms with borrowers, transferring ownership, establishing mortgages, and closing mortgage agreements.An exemplary, non-limiting robotic process automation system may include one or more user interfaces, interfaces with overall system circuits and / or controllers to provide, request, and / or share data, and / or one or more artificial intelligence circuits configured to iteratively improve one or more operations of the robotic process automation system. One of ordinary skill in the art, with the benefit of the disclosure herein and generally available knowledge of contemplated robotic process automation systems, can readily determine the circuits, controllers, and / or devices to include to implement a robotic process automation system that performs selected functions for the contemplated system. Specific examples of robotic process automation systems are described herein for illustrative purposes, however, any embodiment will benefit from the disclosure herein and any considerations that will be understood.

[0299] The term loan-related action (and other related terms such as loan-related event and loan-related activity) is utilized herein and may be understood broadly to describe one or more actions, events, or activities related to a transaction that includes a loan within the transaction. The actions, events, or activities may occur in many different loan contexts, such as lending, refinancing, consolidation, factoring, brokering, foreclosure, administration, negotiation, collection, procurement, enforcement, and data processing (e.g., data collection), or combinations thereof, without limitation. A loan-related action may be used in the noun form (e.g., a notice of default was communicated to a borrower in a formal notice, which would be considered a loan-related action). A loan-related action, event, or activity may refer to a single instance or may characterize a group of actions, events, or activities. For example, a single action, such as giving a specific notice to a debtor who is past due on a payment, may be considered a loan-related action. Similarly, a series of actions from start to finish related to a default may also be considered a single loan-related action. Appraisals, inspections, funding, and records may also be considered, without limitation, any loan-related action that has occurred and any loan-related event. Similarly, activities that complete these actions may also be considered, without limitation, loan-related activities (e.g., appraisals, inspections, funding, records). In certain embodiments, the smart contract or robotic process automation system may process appropriate tasks to perform and complete loan-related actions, loan-related events, or loan-related activities on behalf of one or more of the parties. In some cases, the smart contract or robotic process automation system may not complete the loan-related action, and depending on such outcome, this may enable automated actions or trigger other conditions or clauses.One of ordinary skill in the art, having the benefit of the disclosure herein and knowledgeable about loan-related actions, events, and activities, can readily determine the purpose and use of this term in its various forms and embodiments as described throughout this disclosure.

[0300] Also, the terms loan-related actions, events, and activities herein may be used to more specifically describe the circumstances of a loan call. A loan call is an act by which a lender can request repayment of a loan, usually triggered by some other condition or term, such as a missed payment. For example, a loan-related action may occur when a borrower misses three consecutive payments, causing serious delinquency in the loan payment schedule and causing the loan to default. In such a scenario, the lender may initiate a loan call-related action to protect its rights. In such a scenario, perhaps the borrower would pay an amount to resolve the delinquency or penalty, which would also be considered a loan-related action for a loan call. In some circumstances, a smart contract or robotic process automation system may initiate, manage, or process loan-related actions for a loan call, including but not limited to providing notifications, investigating and collecting payment history, or other tasks performed as part of a loan call. One of ordinary skill in the art, having the benefit of the disclosure herein and knowledgeable regarding loan-related actions for calling a loan, or other forms of this term and its various forms, can readily determine the purpose and use of this term in the context of an event or other various embodiments and contexts disclosed herein.

[0301] As described herein, the terms actions, events, and activities related to a loan may also be used to more specifically describe circumstances related to the payment of a loan. Typically, in transactions involving a loan, including but not limited to, the loan is repaid according to a payment schedule. Various actions may occur to provide the borrower with information to repay the loan and for the lender to receive the loan payment. For example, when a borrower makes a loan payment, a loan-related action may occur for the payment of the loan. Such a payment may include, but is not limited to, a number of actions that occur with respect to the payment of the loan, such as the payment being applied to the lender, a loan ledger or accounting reflecting that the payment has been made, a receipt provided to the borrower for the payment made, and the next payment being requested from the borrower. In some circumstances, a smart contract or robotic process automation system may initiate, manage, or process such loan-related actions for the payment of the loan, which may include, but are not limited to, providing a notice to the lender, researching and collecting payment history, providing a receipt to the borrower, providing a notice of the next payment required from the borrower, or other actions related to the payment of the loan. One of ordinary skill in the art, having the benefit of the disclosure herein and knowledgeable regarding loan-related actions for disbursement of a loan, or other forms of this term and its various forms, can readily determine the purpose and use of this term in the context of an event or other various embodiments and contexts disclosed herein.

[0302] As described herein, the terms actions, events, and activities related to a loan may also be used to more specifically describe the context of a payment schedule or alternative payment schedule. Typically, but not exclusively, in transactions involving loans, the loan is repaid on a payment schedule that may change over time. Alternatively, such a payment schedule may develop and agree upon an alternative payment schedule. For a lender or borrower, various actions may be taken in relation to a payment schedule or alternative payment schedule, such as: the amount of such payment, the due date of such payment, what penalties or fees are attached to late payments, or other terms. For example, if a borrower makes an early payment on a loan, a loan-related action may occur regarding the payment schedule and alternative payment schedule of the loan. In this case, the payment is likely applied as principal, and regular payments will continue to be made. Without limitation, loan-related actions for payment schedules and alternative payment schedules may consist of a number of actions that may occur with respect to the payment of a loan, such as a payment being presented to a lender, a loan ledger or accounting reflecting that a payment has been made, a receipt being provided to the borrower for the payment made, a calculation of whether any fees are attached or paid, and a next payment being requested from the borrower. In certain embodiments, an activity that determines a payment schedule or an alternative payment schedule may be a loan-related action, event, or activity. In certain embodiments, an activity that communicates a payment schedule or an alternative payment schedule (e.g., to a borrower, a lender, or a third party) may be a loan-related action, event, or activity.In some circumstances, smart contract circuitry or robotic process automation systems may initiate, manage, or process such loan-related actions for payment schedules and alternative payment schedules, which may include, but are not limited to, providing notices to lenders, researching and collecting payment history, providing receipts to borrowers, calculating the next payment due date, calculating the final payment amount and due date, providing notice of the next payment due date to borrowers, determining a payment schedule or alternative payment schedule, communicating the payment schedule or alternative payment schedule, or other actions related to the payment of a loan. Those skilled in the art, having the benefit of the disclosure herein and knowledgeable regarding loan-related actions for payment schedules and alternative payment schedules, or other forms of this term and its various forms, can readily determine the purpose and use of this term in the events disclosed herein or in various other embodiments and contexts.

[0303] The term regulatory notice requirement (and its derivatives) as used herein is understood broadly to refer to an obligation or condition to communicate a notice or message to another party or entity. A regulatory notice requirement may be required under one or more triggering conditions or may be generally required. For example, a lender may have a regulatory notice requirement to provide a borrower with notice of a loan default, a change in interest rate on a loan, or other notice related to the transaction or loan. The regulatory aspect of the term may result from jurisdiction-specific laws, rules, or codes that require a specific obligation to communicate. In certain embodiments, a policy directive may be treated as a regulatory notice requirement. For example, a lender may have an internal notice policy that may exceed the regulatory requirements of one or more jurisdictions related to the transaction. The notice aspect generally relates to formal communication and may take a variety of forms, but may be specifically specified with respect to a particular form of notice, e.g., certified mail, facsimile, email transmission, other physical or electronic form, the content of the notice, and / or timing requirements related to the notice. The requirement aspect concerns the need for a party to complete its obligations to comply with a law, regulation, code, policy, standard practice, or the terms of the contract or loan. In certain embodiments, the smart contract may handle or trigger regulatory notification requirements and provide appropriate notice to the borrower. This may be based on at least one of the following locations: the lender, the borrower, the funds provided via the loan, the repayment of the loan, the collateral for the loan, or any other location specified in the terms of the loan, transaction, or contract. If a party or entity fails to meet such regulatory notification requirements, certain changes in the rights or obligations between the parties may be triggered. For example, if a lender provides a notice of non-compliance to a borrower, automated actions or triggers based on the terms of the loan and / or based on external information (e.g., regulatory prescriptions, the lender's internal policies, etc.) may be executed by the smart contract circuitry and / or the robotic process automation system.One of ordinary skill in the art, having the benefit of the disclosure herein and commonly available knowledge of the contemplated systems, can readily determine the purpose and use of regulatory notification requirements in the various embodiments and contexts disclosed herein.

[0304] The term regulatory notice requirement may also be utilized herein to describe an obligation or condition to communicate a notice or message to another party or entity based on a general or specific policy rather than based on a law, rule, or code in a particular jurisdiction or in a particular location (as in jurisdiction-specific regulatory notice requirements). A regulatory notice requirement may be prudent or suggestive rather than mandatory or required, under one or more triggering or generally required conditions. For example, a lender may have a policy-based regulatory notice requirement to notify borrowers of a new informational website, of future changes to interest rates on loans, or other transaction- or loan-related notices that are advisory or helpful rather than mandatory (although mandatory notices may also be policy-based). Thus, in a policy-based use of the term regulatory notice requirement, the smart contract circuitry may process or trigger the regulatory notice requirement and provide appropriate notices to borrowers that may or may not necessarily be required by law, rule, or code. The basis for the notice or communication may be due to prudence, courtesy, custom, or obligation.

[0305] The term regulatory notice may also be used to express an obligation or condition to communicate a notice or message to other parties or entities, such as lenders or borrowers. Regulatory notices may be specifically directed to any party or entity, or group of parties or entities. For example, it may be desirable or necessary to provide a particular notice or communication to a borrower, such as when a borrower defaults as a result of failing to make a loan payment. Such regulatory notices directed to particular users, such as lenders or borrowers, may occur as a result of jurisdiction-specific or policy-based regulatory notice requirements. Thus, in some circumstances, a smart contract may process or trigger a regulatory notice to provide appropriate notice to a particular party, such as a borrower. This notice may or may not necessarily be required by law, regulation, or code, but may be provided based on prudence, civility, or convention. Failure of a party or entity to meet such regulatory notice requirements with respect to a particular party may create a situation in which certain rights may be waived by one or more parties or entities, may enable automated actions, or may trigger other conditions or clauses. One of ordinary skill in the art, having the benefit of the disclosure herein and generally available knowledge of the contemplated systems, will be able to readily determine the purpose and use of regulatory notification requirements based on the various embodiments and contexts disclosed herein.

[0306] The term regulatory foreclosure requirement (and its derivatives) as used herein is understood broadly to refer to obligations or conditions to trigger a loan default, foreclosure or repossession of collateral, or other related foreclosure action. A regulatory foreclosure requirement may be required by one or more triggering conditions or generally required conditions. For example, a lender may have a regulatory foreclosure requirement to provide a borrower with a notice of loan default, or other notice related to a loan default, prior to foreclosure. The regulatory aspect of the term may result from jurisdiction-specific laws, rules, or codes that require specific communication obligations. The foreclosure aspect generally relates to the specific remedy of foreclosure, or repossession of the collateral and default on the loan, which may take many different forms, but may be specified in the terms of the loan. The requirement aspect relates to the need for a party to complete its obligations for compliance with or performance of a law, rule, code, or contract or loan condition. In certain embodiments, smart contract circuitry may process or trigger a regulatory foreclosure requirement and process the appropriate tasks related to such foreclosure action. This may be based on the jurisdictional location of at least one of the lender, borrower, funds provided via the loan, repayment of the loan, and collateral for the loan, or other location specified by the terms of the loan, transaction, or agreement. Certain rights may be waived by a party or entity (e.g., a lender) if the party or entity fails to meet such regulatory foreclosure requirements, or failure to comply with such regulatory notice requirements may enable automated actions or trigger other conditions or clauses. Those skilled in the art, having the benefit of the disclosure herein and generally available knowledge of the contemplated systems, can readily determine the purpose and use of regulatory foreclosure requirements in the various embodiments and contexts disclosed herein.

[0307] The term regulatory foreclosure requirement may also be used to refer to or be used to refer to an obligation to cause a loan default, foreclosure or repossession of collateral, or other related foreclosure action; to be general or specific policy-based, rather than based on a law, regulation, or code in a particular jurisdiction, or in a particular location (as in jurisdiction-specific regulatory foreclosure requirements); and to be prudent, suggested, or generally required, rather than mandatory or required, under one or more triggering conditions. For example, a lender may have a policy-based regulatory foreclosure requirement to provide a borrower with notice of a loan default, or to provide other notices related to the transaction or loan that are advisory or helpful, but not mandatory (although mandatory notices may also be policy-based). Thus, in a policy-based use of the regulatory foreclosure requirement term, a smart contract may process or trigger a regulatory foreclosure requirement and provide appropriate notices to the borrower, even though they may not necessarily be required by law, regulation, or code. The basis for notice or communication may be prudence, courtesy, custom, industry practice, or obligation.

[0308] The term regulatory foreclosure requirements may also be used herein to express obligations or conditions to be performed with respect to particular users, such as lenders or borrowers. Regulatory notices may be specifically directed to any party or entity, or group of parties or entities. For example, it may be desirable or necessary to provide a particular notice or communication to a borrower, such as when a borrower defaults as a result of failing to make scheduled payments on a loan. As such, such regulatory foreclosure requirements may be directed to particular users, such as lenders or borrowers, and may be the result of jurisdiction-specific regulatory foreclosure requirements, or policy-based regulatory foreclosure requirements, or the like. For example, foreclosure requirements may relate to particular entities involved in a transaction (e.g., current borrowers are uniquely treated because they have been customers for 30 years), or classes of entities (e.g., "preferred" borrowers, or "first-time defaulting" borrowers). Thus, in some circumstances, smart contract circuitry may process or trigger obligations or actions that must be taken pursuant to a foreclosure, which actions may or may not be dictated by a particular party, such as a lender or borrower, or may not necessarily be required by law, regulation, or code, but may otherwise be provided out of prudence, courtesy, or convention. In certain embodiments, an obligation or condition to be performed with respect to a particular user may form part of a contract or otherwise be known to the particular user to which it applies (e.g., a bank may have a policy that relates to a class of users to which a particular user belongs, but the particular user may not be aware of that class).

[0309] Value, valuation, valuation model (and similar terms) utilized herein should be understood broadly to describe an approach to valuing and determining the estimated value of collateral. Without being limited to other aspects or descriptions of this disclosure, the valuation model may be used in combination with collateral (e.g., collateral property), artificial intelligence services (e.g., to improve the valuation model), data collection and monitoring services (e.g., to set valuations), valuation services (e.g., a process to inform, use, and / or improve the valuation model), and / or results related to transactions of collateral (e.g., as a basis for improving the valuation model). "Jurisdiction-specific valuation model" is also used as a valuation model used in a particular geographic / jurisdictional area or region, where the jurisdiction may be specific to the lender, borrower, delivery of funds, disbursement of the loan, or the jurisdiction of the collateral for the loan, or a combination thereof. In certain embodiments, the jurisdiction-specific valuation model considers the impact of jurisdiction on the valuation of the collateral. This includes, at a minimum, the rights and obligations of the borrower and lender in the relevant jurisdiction, the impact of the jurisdiction on the ability to move, import, export, substitute, and / or liquidate the collateral, the impact of the jurisdiction on the timing between default and seizure or recovery of the collateral, and / or the impact of the jurisdiction on the volatility and / or sensitivity of collateral value determinations. In certain embodiments, a geographic location specific valuation model considers the impact of geographic location on the valuation of the collateral. This may include a similar list of jurisdictional impacts (however, the location of the jurisdiction may differ from the geographic location), but may include additional impacts such as weather related impacts, the distance of the collateral from monitoring, maintenance, or seizure services, and / or the proximity of risk phenomena (e.g., faults, industrial areas, nuclear power plants, etc.). The valuation model may utilize offset collateral valuations (e.g., general values ​​such as similar items of the collateral, market values ​​of similar or forgivable collateral, and / or values ​​of items that correlate with the value of the collateral) as part of the valuation of the collateral.In certain embodiments, the artificial intelligence circuitry includes one or more machine learning and / or artificial intelligence algorithms, including utilizing information over time between multiple transactions, e.g., involving similar or offsetting collateral, to improve the valuation model, and / or utilizing outcome information from the same transaction or other transactions (e.g., when a loan transaction is completed successfully or unsuccessfully, and / or indicative of real-world collateral valuation decisions, corresponding to collateral foreclosure or liquidation events) to iteratively improve the valuation model. In certain embodiments, the artificial intelligence circuitry is trained through interaction with a collateral valuation dataset, e.g., previously determined valuations, and / or a trainer (e.g., human, accounting valuations, and / or other valuation data). In certain embodiments, the valuation model and / or parameters of the valuation model (e.g., assumptions, calibration values, etc.) may be determined and / or negotiated as part of the terms of the transaction (e.g., loan, set of loans, and / or subset of set of loans). Those skilled in the art, having the benefit of the disclosure herein and with commonly available knowledge of the contemplated system, can easily determine which aspects of the disclosure herein benefit a particular application of the valuation model and how to select or combine valuation models to implement an embodiment of the valuation model. Specific considerations for those skilled in the art in selecting an appropriate valuation model or for an embodiment of the disclosure include, but are not limited to, the following: legal considerations of the valuation model considering the jurisdiction of the collateral, available data for a given collateral, expected transaction / loan type, specific collateral type, loan to value ratio, collateral to loan ratio, total transaction / loan amount, borrower credit score, loan type and / or related industry accounting practices, uncertainties related to any of the above, and / or sensitivities related to any of the above. Specific examples of valuation models and considerations are described herein for illustrative purposes, but any embodiment having the benefit of the disclosure herein and any considerations understood by one skilled in the art having the benefit of the disclosure herein are specifically contemplated within the scope of the disclosure.

[0310] As used herein, the term "market value data" or "market information" (and other forms or variations) is understood broadly to refer to any data or information related to the valuation of real estate, assets, collateral, or other items of value that may be used as the subject of a loan, security, or transaction. Market value data or market information may change from time to time and may be estimated, calculated, objectively or subjectively determined from a variety of sources. Market value data or market information may relate directly to the item of collateral or may relate to the item of collateral offset by it. Market value data or market information may include financial data, market valuations, product valuations, customer data, market research to understand customer needs and preferences, competitive information such as competitors and suppliers, an entity's sales, transactions, customer acquisition costs, customer lifetime value, brand awareness, churn rates, and the like. The term may occur in many different contexts of contracts and loans, including, but not limited to, lending, refinancing, consolidation, factoring, brokerage, foreclosure, data processing (e.g., data collection), and combinations thereof. Market value data or market information may be used as a noun to identify a single number or multiple numbers or data. For example, without being limited to these circumstances, the market value data or market information may be utilized by a lender to determine whether a property or asset will serve as collateral for a secured loan, or alternatively, in foreclosure decisions if a loan is in default. The market value data or market information may also be used to determine a loan-to-value figure or calculation. In certain embodiments, the collection service, smart contract circuitry, and / or robotic process automation system may estimate or calculate the market value data or market information from one or more sources of data or information. In some cases, the value or market information of the market data may enable automated actions or trigger other conditions or clauses depending on the data / information contained therein.One of ordinary skill in the art, having the benefit of this disclosure and typically available knowledge of the contemplated systems and relevant market information available, will be able to readily determine the purpose and use of the terms in the various forms, embodiments, and contexts disclosed herein.

[0311] As used herein, terms such as similar collateral, similar to collateral, offset collateral, and the like are understood broadly to describe property, assets, or items of value that may be similar in nature to collateral (e.g., items of value held as security) in connection with a loan or other transaction. Similar collateral refers to property, assets, collateral, or other items of value that are aggregated, substituted, or otherwise referenced together with other collateral. This may be in the form of common attributes such as the history of the collateral, ownership of the collateral, custodianship of the collateral, security of the collateral, status of the owner of the collateral, liens on the collateral, storage status of the collateral, geographic location of the collateral, or jurisdictional location of the collateral. In certain embodiments, offset collateral refers to items that are correlated in value to the items of collateral. For example, offset collateral may exhibit similar price fluctuations, volatility, storage requirements, etc., as the items of collateral. In some embodiments, similar collateral may be aggregated to form a larger security interest and serve as collateral for additional loans, distributions, or transactions. In certain embodiments, offset collateral may be utilized to inform the valuation of the collateral. In certain embodiments, the smart contract circuitry or robotic process automation system may estimate or calculate values, data or information related to similar collateral or perform functions related to the aggregation of similar collateral. One of ordinary skill in the art, given the benefit of the disclosure herein and with generally available knowledge of the contemplated systems, can readily determine the purpose and use of similar collateral, offsetting collateral, or related terms as they relate to collateral in the various forms, embodiments, and contexts disclosed herein.

[0312] As used herein, the term restructuring (and other forms such as restructuring) is broadly understood to mean modifying the terms, property, collateral, or other considerations affecting a loan or transaction. Restructuring may be successful, with the parties adopting modified terms, or it may fail without modification or restructuring. Restructuring may occur at various points in a contract or loan, including, but not limited to, application, lending, refinancing, collection, consolidation, factoring, brokerage, and foreclosure. In addition, restructuring of debt means that debt owed to a party is modified in terms of timing, amount, collateral, or other terms. For example, a borrower may restructure a loan obligation to accommodate a change in financial circumstances, and a lender may offer a borrower a restructuring of its debt for its own needs or prudence. In certain embodiments, the smart contract circuitry or robotic process automation system may automatically or manually restructure debt based on monitored conditions, create options to restructure debt, manage the process of negotiating or executing debt restructurings, or take other actions related to restructuring or amending the terms of a loan or transaction. One of ordinary skill in the art, having the benefit of the disclosure herein and generally available knowledge of the contemplated systems, can readily determine the purpose and use of this term in the various embodiments and contexts disclosed herein, whether or not in the context of debt.

[0313] As used herein, social network data collection, social network monitoring services, and social network data collection and monitoring services (and various forms and derivatives thereof) may be broadly understood to refer to services related to obtaining, organizing, observing, and otherwise acting on data and information obtained from one or more social networks. The social network data collection and monitoring services may be part of a related service system or may be a separate set of services. The social network data collection and monitoring services may be provided by a platform or a system, without limitation. The social network data collection and monitoring services may be used in a variety of contexts, including, without limitation, lending, refinancing, negotiating, collecting, consolidating, factoring, brokering, foreclosure, and combinations thereof. Requests for social network data collection and monitoring may be requested by other services, initiated automatically, or triggered to occur based on conditions or circumstances that occur, with configuration parameters. Interfaces may be provided for configuring, initiating, viewing, or otherwise interacting with the social network data collection and monitoring services. As used herein, a social network refers to any mass platform where data and communication occurs between individuals and / or entities, and where the data and communication is at least partially accessible to an embodiment system. In certain embodiments, social network data includes information that is publicly available (e.g., accessible without any permission). In certain embodiments, social network data includes information that is appropriately accessible to an embodiment system, but may include subscription access or other access to information that is not publicly freely available but is accessible (e.g., consistent with a privacy policy with users of the social network). Social networks may be primarily social in nature, but may additionally or alternatively include professional networks, alumni networks, industry-related networks, academically oriented networks, etc.In certain embodiments, the social network may be a crowdsourcing platform, e.g., a platform configured to accept queries or requests directed to users (and / or potentially a subset of users meeting specified criteria), where the users may know that a particular communication will be shared and accessible to at least a portion of the requester, users of the platform, and / or be publicly available. In certain embodiments, without limitation, the social network data collection and monitoring service may be performed by a smart contract circuit or a robotic process automation system. One of ordinary skill in the art, with the benefit of the disclosure herein and generally available knowledge of the contemplated systems, may readily determine the purpose and use of the social network data collection and monitoring service in the various embodiments and contexts disclosed herein.

[0314] The term crowdsourced and social network information as utilized herein may further be understood broadly to describe information obtained or provided in connection with a crowdsourcing model or transaction, or obtained or provided on or in connection with a social network. The crowdsourced and social network information may be provided by, without limitation, a platform or system. The crowdsourced and social network information may be obtained, provided, or communicated to or from a group of information providers, whereby responses to requests may be collected and processed. The crowdsourced and social network information may provide information, terms, or factors related to a loan or contract. The crowdsourced and social network information may be, without limitation, private or public, or a combination thereof. In certain embodiments, without limitation, the crowdsourced and social network information may be obtained, provided, organized, or processed by smart contract circuitry, and the crowdsourced and social network information may be managed by smart contract circuitry that processes the information to satisfy a set of configured parameters. One of ordinary skill in the art, having the benefit of the disclosure herein and generally available knowledge of the contemplated systems, can readily determine the purpose and use of the term in the various embodiments and contexts disclosed herein.

[0315] As used herein, the word "negotiate" (and other forms such as negotiating and negotiation) is understood broadly to refer to discussions or communications between parties or entities to effect a compromise, outcome, or agreement. Negotiations may result in a successful outcome where terms are agreed upon between the parties, or in an unsuccessful outcome where the parties do not agree to certain terms, or any combination thereof. Negotiations may be successful in one aspect or for a particular purpose, and unsuccessful in another aspect or for a different purpose. Negotiations may occur in various aspects of a contract or loan, including, but not limited to, lending, refinancing, collection, consolidation, factoring, mediation, and foreclosure. For example, a borrower may negotiate interest rates and loan terms with a lender. In another example, a defaulting borrower may negotiate with a lender an alternative solution to avoid foreclosure. In particular, In certain embodiments, the smart contract circuitry or robotic process automation system may negotiate on behalf of one or more of the parties and process appropriate tasks to complete or attempt to complete the negotiation of the terms. In some cases, negotiation by the smart contract or robotic process automation system may not be completed or successful. Successful negotiation may enable automated actions or trigger other conditions or clauses that are implemented by the smart contract circuitry or robotic process automation system. One of ordinary skill in the art, having the benefit of the disclosure herein and generally available knowledge of the contemplated systems, can readily determine the purpose and use of negotiation in the various embodiments and contexts disclosed herein.

[0316] The term negotiation in its various forms may be utilized herein, more specifically, in verb form (e.g., to negotiate) or noun form (e.g., negotiation) to describe the context of mutual discussion leading to an outcome. For example, the robotic process automation system may negotiate terms on behalf of the parties, which would be its use as a verb clause. In another example, the robotic process automation system may negotiate terms for a loan modification, negotiate an integration offer, or other terms. As a noun clause, the negotiation (e.g., an event) may be performed by the robotic process automation system. Thus, in some circumstances, the smart contract circuit or robotic process automation system may negotiate terms (e.g., as a verb clause) or a description of doing so may be considered a negotiation (e.g., as a noun clause). One of ordinary skill in the art, having the benefit of the disclosure herein and knowledge of negotiation and negotiation, or other forms of the word negotiation, may readily determine the purpose and use of the term in the various embodiments and contexts disclosed herein.

[0317] Various forms of the term negotiate may also be utilized to specifically refer to a mutual compromise or to a mutually agreed upon outcome, such as the completion of negotiations that result in a result. For example, a loan may be considered negotiated as a successful outcome of the parties reaching an agreement upon completion of the negotiations, such as by a robotic process automation system. Thus, in some circumstances, a smart contract circuit or a robotic process automation system may be negotiating a set of terms or to complete a negotiated loan. One of ordinary skill in the art, having the benefit of the disclosure herein and generally available knowledge of the contemplated systems, may readily determine the purpose and use of the term as it relates to a mutually agreed upon outcome upon completion of negotiations in the various embodiments and contexts disclosed herein.

[0318] Additionally, various forms of the term negotiate may be used to specifically characterize events such as negotiation events, or events that involve reaching mutually agreeable terms between parties. Any event that requires agreement or compromise between parties may be considered a negotiation event, without limitation. For example, the process of reaching a mutually agreeable set of terms between parties when procuring a loan may be considered a negotiation event. Thus, in some circumstances, smart contract circuitry or robotic process automation systems may respond to the parties' communications, actions, or behaviors for a negotiation event.

[0319] As used herein, the term "collection" (and other forms such as "collect" or "collecting") is understood broadly to refer to the acquisition of a tangible (e.g., physical item), intangible (e.g., data, license, or rights), or monetary (e.g., payment) item, or other obligation or asset, from a source. In general, the term may relate to the entire prospect of acquiring such item, from early stage related work to later stage related work, or full completion of the acquisition of the item. Collection may be, but is not limited to, the successful outcome of an item being bid to a party, or the unsuccessful outcome of an item not being bid to or acquired by a party, or a combination thereof (e.g., an item being bid late or otherwise deficiently). Collection may occur in various aspects of a contract or loan, including, but not limited to, lending, refinancing, consolidation, factoring, brokerage, foreclosure, and data processing (e.g., data collection). Collection may be used in the form of a noun (e.g., when referring to or characterizing an event, such as data collection or collection of overdue fees), may refer to an assortment of items as a noun (e.g., when referring to a number of items in a transaction, such as collection of collateral for a loan), or may be used in the form of a verb (e.g., when collecting payment from a borrower). For example, a lender may collect overdue fees from a borrower via an online payment or may successfully collect overdue fees obtained via a customer service call. In certain embodiments, the smart contract circuitry or robotic process automation system may perform collections on behalf of one or more of the parties and process appropriate tasks to complete or attempt collections on one or more items (e.g., overdue fees). In some cases, negotiations by the smart contract or robotic process automation system may not be completed or successful, and depending on such outcome, this may enable automated actions or trigger other conditions or clauses.One of ordinary skill in the art, having the benefit of the disclosure herein and generally available knowledge of the contemplated systems, will be able to readily determine the purpose and use of collection in the various forms, embodiments, and contexts disclosed herein.

[0320] Also, the term collection in its various forms may be utilized herein in the noun form to more specifically describe the context of an event or thing, such as a collection event, or collection payment. For example, a collection event may refer to, but is not limited to, contacting a party or other activity related to the acquisition of an item in the activity. A collection payment may, for example, relate to a payment made by a borrower that is obtained in the course of collection or through a collection department with a lender. Although not limited to overdue, delinquent, or defaulted loans, collection may characterize an event, payment or department, or other noun related to a transaction or loan, as a remedy for something that has become delinquent. Thus, in some circumstances, a smart contract circuit or robotic process automation system may collect a payment or installment from a borrower, and the activity of doing so may, without limitation, be considered a collection event.

[0321] Various forms of the term collection may also be utilized herein, more specifically, as an adjective or other term to describe a litigation-related context, such as the outcome of a collection action (e.g., an action regarding past due or unpaid loan amounts). For example, the outcome of a collection action may relate to past due amounts owed by a borrower or other party, and collection efforts related to those past due amounts may be litigated by the party. Thus, in some circumstances, smart contract circuitry or robotic process automation systems may receive, determine, or otherwise manage the outcome of a collection action.

[0322] Also, the term collection in its various forms may be utilized herein more specifically as an adjective or the like to denote a context relating to a taking action, such as a collection action (e.g., an action to induce the tender or taking of delinquent or defaulted payments on an obligation, such as a loan). The terms collection yield, collection financial yield, and / or collection financial yield may be used. The outcome of such a collection action may or may not have a financial yield. For example, a collection action may result in one or more outstanding amounts on a loan being paid, which may result in a financial yield to another party, such as a lender. Thus, in some circumstances, a smart contract circuit or robotic process automation system may render a financial yield from a collection action or may otherwise manage or in some way assist in the financial yield of a collection action. In an embodiment, a collection action may include the need for collection litigation.

[0323] Also, various forms of the term collection (such as collection ROI, ROI for collection, ROI for collection activity, collection activity ROI, etc.) may be used herein to more specifically describe contexts relating to value-receiving actions, such as collection actions with a return on investment (ROI) (e.g., actions that induce tendering or obtaining delinquent or defaulted payments on loans or other obligations). The outcome of such collection actions may or may not have an ROI, either in terms of the collection action itself (ROI for collection action), or in terms of the broader loan or transaction that is the subject of the collection action. For example, the ROI of a collection action may be prudent or unwise with respect to defaulted loans, depending on whether an ROI is provided to a party, such as a lender, without limitation. A predicted ROI for collections may be estimated or calculated taking into account actual events that pass. In some circumstances, a smart contract circuit or robotic process automation system may render an estimated ROI for a collection action or collection event, or may calculate an ROI for actual events that pass in the collection action or collection event, without limitation. In an embodiment, such ROI, whether estimated or actual, may be a positive or negative numerical value.

[0324] Terms such as reputation, reputation measure, lender reputation, borrower reputation, entity reputation, and the like may include common and widely held beliefs, opinions, and / or perceptions commonly held about an individual, entity, collateral, and the like. Reputation measures may be determined based on social data including likes and dislikes, reviews of the entity or products and services the entity offers, company or product rankings, current and historical market and financial data (including prices, forecasts, buy and sell recommendations, financial news about the entity, competitors, and partners). Reputation may be cumulative in that product reputation, reputation of company leaders and lead scientists affect the overall reputation of the company. Reputation of institutions associated with the entity (e.g., schools attended by students) may affect the entity's reputation. In some circumstances, the smart contract circuit or robotic process automation system may collect, or begin to collect, data related to the above to determine a reputation measure or ranking. The entity's reputation measure or ranking may be used by the smart contract circuit or robotic process automation system in deciding whether to enter into a contract with the entity, determining the terms of a loan, determining interest rates, and the like. In certain embodiments, the reputation determination metric may determine a measure or ranking of an entity's reputation in relation to one or more transaction outcomes (e.g., a comparison of "likes" in a particular social media data set to outcome metrics such as successful payments, successful negotiation outcomes, ability to liquidate a particular type of collateral, etc.). One of ordinary skill in the art, having the benefit of the disclosure herein and generally available knowledge of the contemplated systems, can readily determine the purpose and use of reputation, reputation measurements or rankings, and / or the use of reputation in negotiations, determining terms, determining whether to proceed with a transaction, and various other embodiments and contexts disclosed herein.

[0325] The term collections in various forms (e.g., collectors) may also be used more specifically herein to describe parties or entities that induce, manage, or facilitate collection actions, collection events, or other collection-related contexts. A measure of reputation of a party, such as a collector, or in the context of a collection may be estimated or calculated using objective, subjective, or historical metrics or data. For example, a collector may be involved in a collection action and the reputation of that collector may be used to determine decisions, actions, or conditions. Similarly, collections may also be used to describe objective, subjective, or historical metrics or data to measure the reputation of a party, such as a lender, borrower, or debtor. In some circumstances, smart contract circuitry or robotic process automation systems may render collections or measures or implement collectors within the context of a transaction or loan.

[0326] Also, the terms collection and data collection in various forms, including data collection systems, may be utilized more specifically herein to describe, without limitation, contexts related to the acquisition, organization, processing, or combinations thereof of data. The results of such data collection may relate to the collection of items (e.g., grouping items physically or logically), or to actions taken on delinquencies (e.g., collecting collateral, debt, etc.), or may not relate at all. For example, data collection may be performed by a data collection system, where data is acquired, organized, or processed for prospective or actual trading or lending decision-making, monitoring, or other purposes. In some circumstances, smart contracts or robotic process automation systems may incorporate data collection or data collection systems to perform some or all of the tasks of data collection, including, but not limited to, those skilled in the art, having the benefit of the disclosure herein and generally available knowledge of the contemplated systems, may readily determine and distinguish the purpose and use of collection in the context of data or information as used herein.

[0327] As utilized herein, refinancing, refinancing activity(ies), refinancing interactions, refinancing results, and similar terms should be understood broadly. Without being limited to other aspects or explanations of this disclosure, refinancing and refinancing activities include replacing an existing mortgage, loan, bond, debt transaction, or the like with a new mortgage, loan, bond, or debt transaction that pays off or terminates the previous financial arrangement. In certain embodiments, any change to the terms of the loan and / or any material change to the terms of the loan may be considered a refinancing activity. In certain embodiments, refinancing activities are considered only those changes to the loan agreement that result in a different financial outcome of the loan agreement. Typically, the new loan should be favorable to the borrower or issuer and / or should be mutually agreeable (e.g., improving the raw financial results of one and improving the securities or other results of the other). Refinancing may be done to reduce interest rates, lower periodic payments, change the loan term, change the collateral associated with the loan, consolidate debt into a single loan, restructure debt, change the type of loan (e.g., from a variable rate to a fixed rate), pay off loans as they come due, expand loans in response to improving credit scores, and / or in response to changes in market conditions (e.g., interest rates, collateral values, etc.).

[0328] Refinancing activities include initiating a refinancing offer, initiating a request for refinancing, setting a refinancing interest rate, setting a refinancing payment schedule, setting a refinance balance according to the amount or terms of the refinanced loan, setting up collateral for the refinance including changing the collateral used, changing the terms of the collateral, changing the collateral amount, etc., managing the use of the refinance proceeds, granting liens on different items of collateral as necessary if the terms are changed as part of the refinance, verifying ownership of the collateral of new or existing items used to secure the refinanced loan, managing the inspection process of ownership of the collateral of new or existing items used to secure the refinanced loan, preparing a loan refinancing application, negotiating the terms of the refinanced loan, and completing the refinance. Refinancing and refinancing activities may be disclosed in the context of a data collection and monitoring service that collects a training set of interactions between entities for a set of loan refinancing activities. Refinancing and refinancing activities may be disclosed in the context of an artificial intelligence system that is trained using the training set of collected interactions including both refinancing activities and outcomes. The trained artificial intelligence may then be used to recommend refinancing activities, evaluate refinancing activities, predict likely outcomes of refinancing activities, etc. Refinancing and refinancing activities may be disclosed in the context of a smart contract system that may automate a subset of refinancing interactions and activities. In one example, the smart contract system may automatically adjust the interest rate of the loan based on information collected via at least one of an Internet of Things system, a crowdsourcing system, a set of social network analysis services, and a set of data collection and monitoring services. The interest rate may be adjusted based on rules, thresholds, model parameters that determine or recommend an interest rate for refinancing the loan based on interest rates available to the lender from secondary lenders, borrower risk factors (including predicted risk based on one or more predictive models using artificial intelligence), marketing factors (e.g., competing interest rates offered by other lenders), etc.The outcomes and events of the refinancing activity may be recorded on the distributed ledger. Based on the outcome of the refinancing activity, the smart contract for the refinancing loan may be automatically reconfigured to define the terms of the new loan, such as the debt principal, the debt balance, the fixed interest rate, the floating interest rate, the payment amount, the payment schedule, and the balloon payment schedule. The terms of the new loan, such as the collateral designation, the collateral fungibility designation, the parties, guarantees, guarantors, collateral, personal guarantees, liens, duration, covenants, lien conditions, default conditions, and default consequences, may be automatically reconfigured.

[0329] Those skilled in the art, having the benefit of the disclosure herein and generally available knowledge of the contemplated systems, can readily determine which aspects of the present disclosure benefit from a particular application of a refinancing activity, how to select or combine refinancing activities, how to implement a system, service, or circuit that automatically performs one or more (or all) aspects of a refinancing activity, etc., and can readily determine the specific considerations for an embodiment of the present disclosure, or in selecting an appropriate training set of interactions for training an artificial intelligence to take, recommend, or predict the outcome of a particular refinancing activity. While specific examples of refinancing and refinancing activities are described herein for illustrative purposes, any embodiment having the benefit of the disclosure herein, and any considerations understood by a person skilled in the art having the benefit of the disclosure herein, are specifically contemplated within the scope of the present disclosure.

[0330] As utilized herein, the terms aggregation, aggregation activity, loan aggregation, debt aggregation, aggregation plan, and similar terms should be understood broadly. Without being limited to other aspects or explanations of the present disclosure, consolidation, consolidation activity(ies), loan consolidation, debt consolidation, consolidation plan relate to using a single larger loan to pay off multiple smaller loans and / or using one or more of a set of loans to pay off at least a portion of one or more of a second set of loans. In an embodiment, the consolidation of loans may be secured (i.e., backed by collateral) or unsecured. Loan consolidation may be undertaken to obtain a lower interest rate than one or more current loans, to reduce the total monthly loan payments, and / or to bring debtors into compliance with the consolidated loans or other debtors' obligations. Loans classified as candidates for consolidation may be determined based on a model that processes attributes of the entities involved in a set of loans, such as the identity of the parties, interest rates, payment balances, payment tempo, payment schedule, loan type, type of collateral, financial status of the parties, payment status, status of the collateral, and value of the collateral. Consolidation activities may include managing at least one of identifying loans from a set of candidate loans, preparing a consolidated offer, preparing a consolidation plan, preparing content to communicate the consolidated offer, scheduling the consolidated offer, communicating the consolidated offer, negotiating amendments to the consolidated offer, preparing a consolidation agreement, executing the consolidation agreement, amending collateral for the set of loans, processing an application workflow for consolidation, managing inspections, managing appraisals, setting interest rates, deferring payment requirements, setting payment schedules, and entering into a consolidation agreement. In an embodiment, there may be systems, circuits, and / or services configured to create, configure (e.g., using one or more templates or libraries), modify, set, or otherwise process various rules, thresholds, conditional procedures, workflows, model parameters, etc. to determine or recommend a consolidation action or plan for a loan transaction or set of loans based on one or more events, conditions, states, actions, etc.In an embodiment, the consolidation plan may be based on a variety of factors, such as the status of payments, the interest rates for the set of loans, the prevailing interest rates in the platform market or external markets, the status of the borrowers for the set of loans, the status of the collateral or assets, risk factors of the borrowers, lenders, one or more guarantors, market risk factors, etc. Consolidation and consolidation activities may be disclosed in the context of a data collection and monitoring service that collects a training set of interactions between entities for a set of loan consolidation activities. Consolidation and consolidation activities may be disclosed in the context of an artificial intelligence system that is trained using the training set of collected interactions, including both consolidation activities and outcomes related to those activities. The trained artificial intelligence may then be used to recommend consolidation activities, evaluate consolidation activities, make predictions regarding the likely outcomes of consolidation activities, etc., based on models that include the status of the debt, the status of the collateral or assets used to secure or back the set of loans, the status of the business or operations (e.g., receivables, debt, etc.), the status of the parties (e.g., net worth, wealth, debt, location, other status, etc.), the behavior of the parties (e.g., behaviors indicative of preferences, behaviors indicative of debt preferences, behaviors, etc.), etc. Debt restructuring, loan restructuring, and related restructuring activities may be disclosed in the context of a smart contract system that can automate a subset of restructuring interactions and activities. In embodiments, consolidation may include consolidating on terms of a set of loans, selecting appropriate loans, setting payment terms for linked loans, setting payoff plans for existing loans, communicating to facilitate the consolidation, etc.In embodiments, the smart contract's artificial intelligence may automatically recommend or set rules, thresholds, actions, parameters, etc. (optionally by learning to do so based on a training set of results over time), resulting in a recommended integration plan, which may specify a course of actions necessary to achieve the integration recommendation or desired outcome (e.g., within a range of acceptable outcomes), which may be automated and may include conditional execution of steps based on monitored conditions and / or smart contract conditions, which steps may be created, configured, and / or accounted for by the integration plan, resulting in a recommended integration plan. The consolidation plan may be determined and executed based on at least one of market factors (competitive interest rates offered by other lenders, value of collateral, etc.) and regulatory and / or compliance factors. Consolidation plans may be generated and / or executed for the creation of new consolidated loans, secondary loans related to consolidated loans, amendments to existing loans related to consolidation, modifications to the terms of consolidated loans, foreclosure situations (e.g., changing from secured loan rates to unsecured loan rates), bankruptcy or insolvency situations, situations involving market changes (e.g., changes in prevailing interest rates), etc.

[0331] Some of the activities related to loans, collateral, entities, etc. may apply to a wide variety of loans and may not be explicitly applied to consolidation activities. Classification of an activity as a consolidation activity may be made based on the context of the loan for which the activity is being performed. However, one of ordinary skill in the art with the benefit of the disclosure herein and generally available knowledge of the contemplated systems can readily determine which aspects of the present disclosure would benefit from a particular application of consolidation activities, how to select or combine consolidation activities, how to implement selected services, circuits, and / or systems described herein to perform a particular loan consolidation operation, etc. While specific examples of consolidation and consolidation activities are described herein for illustrative purposes, any embodiment benefiting from the disclosure herein, and any considerations understood by one of ordinary skill in the art with the benefit of the disclosure herein, are specifically contemplated within the scope of the present disclosure.

[0332] As used herein, terms such as loan factoring, loan transaction factoring, factor, loan interaction factoring, factoring assets or set of assets used in factoring, and similar terms should be understood broadly. Without being limited to other aspects or explanations of this disclosure, factoring may apply to the factoring of assets such as invoices, inventory, accounts receivable, etc., where the realizable value of the item is in the future. For example, accounts receivable are more valuable when they are paid for and there is less risk of default. Inventory and work in progress (WIP) may be more valuable as finished products rather than parts. The term accounts receivable should be understood to encompass these terms and is not limiting. Factoring involves selling accounts receivable at a discount to their current value (often cash). Factoring also involves using accounts receivable as collateral for short-term financing. In either case, the value of the accounts receivable or invoice may be discounted for multiple reasons, such as the future value of money, the term of the accounts receivable (e.g., 30-day net payment vs. 1-year net payment), etc. Discounts can be applied for several reasons, including the tenor of the receivables payable within 30 days vs. 90 days (e.g. 30 days net pay vs. 90 days net pay), the degree of risk of default on the receivables, the status of the receivables, the status of work in process, the status of inventory, the delivery / shipment status, the financial status of the party owed money on the receivables, the shipping / billing status, and the payment status. payment status, status of borrower, status of inventory, risk factors of borrower, lender and / or guarantor, market risk factors, status of debt (whether there are other liens on receivables and / or inventory payables), status of secured assets (e.g., status of inventory (e.g., is inventory current or not current, is invoices up to date), business and management status, status of the parties to the transaction (e.g., net worth, assets, liabilities, location, etc.), behavior of the parties to the transaction (indicates preferences, behavior, negotiating style, behavior, etc.), current interest rates, current regulatory and compliance issues relating to inventory and / or receivables (e.g., is inventory factored, not factored), market risk factors.In the case of factoring inventory, the information includes many factors, including prediction of risk based on one or more predictive models using artificial intelligence, such as whether the intended product has the proper approvals, legal action against the borrower, etc. Factoring refers to an individual, company, entity, or group of persons who agree to provide value for acquisition by sale of invoices or for financing secured by invoices. Factoring includes identifying candidates (lenders and borrowers) to be factored, a factoring plan specifying the proposed receivables (all, some, or only those that meet certain conditions) and the proposed discount rate, communicating the plan to the candidates, making offers and receiving offers, checking the quality of the receivables, and terms regarding the handling of the receivables during the loan period. Although specific examples of factoring and factoring activities are described herein for illustrative purposes, any embodiment having the benefit of the disclosure herein, and any considerations that would be understood by one of ordinary skill in the art having the benefit of the disclosure herein, are specifically contemplated within the scope of this disclosure.

[0333] As used herein, the terms mortgage, mortgage brokerage, mortgage securing, mortgage financing activities, and / or mortgage-related activities are to be understood broadly. Without being limited to any other aspect or explanation of this disclosure, a mortgage is an exchange in which a borrower provides an item of value, typically ownership of real property or a lien on ownership, to a lender as collateral in exchange for money or another item of value, typically to be repaid with interest. The exchange includes a condition that ownership reverts to the borrower upon repayment of the loan and / or that the lien on the real property is removed. Mortgage brokerage may include identifying potential real property, lenders, and other loan parties, and arranging and negotiating the terms of the mortgage. Certain components and activities may not be considered related to mortgage loans individually, but may be considered related to mortgage loans when used in connection with mortgage loans, when acting on mortgage loans, when relating to mortgage loan entities or parties, etc. For example, brokerage may apply to the offering of various loans, including unsecured loans, outright sales of real property, etc. Mortgage activities and mortgage interactions may include, but are not limited to, mortgage marketing activities, identifying potential borrowers, identifying properties to be mortgaged, identifying collateral properties to be mortgaged, qualifying borrowers, title searches and / or title checks on properties to be mortgaged, appraisals of properties to be mortgaged, property inspections, or property valuations, income verification, demographic analysis of borrowers, identifying capital providers, determining available interest rates, determining available payment terms, analysis of existing mortgages, comparative analysis of existing mortgage terms and new mortgage terms, completing the application workflow (e.g., initiating next steps as necessary to advance the application), extracting application fields, preparing a mortgage agreement, completing a mortgage agreement schedule, negotiating mortgage terms with capital providers, negotiating mortgage terms with borrowers, transferring ownership, granting a lien on the mortgaged property, executing a mortgage agreement, and similar terms as used herein should be understood broadly.Although specific examples of mortgages and mortgage brokerage are described herein for purposes of illustration, any embodiment having the benefit of the disclosure herein, and any considerations that would be understood by a person of ordinary skill in the art having the benefit of the disclosure herein, is specifically contemplated within the scope of the disclosure.

[0334] As utilized herein, the terms debt management, debt transactions, debt actions, debt terms, debt syndication, debt consolidation, and / or debt portfolio should be understood broadly. Without being limited to other aspects or explanations of this disclosure, debt includes anything of monetary value that is owed to another party. A loan typically results in a borrower having a liability (e.g., money that must be repaid according to the terms of the loan, which may include interest). Debt consolidation involves using a new single loan to repay multiple loans (or various debt structuring configurations as described herein and understood by those skilled in the art). Often the new loan may have better terms or a lower interest rate. A debt portfolio includes many pieces or groups of debt with different characteristics including term, risk, etc. Managing a debt portfolio may include decisions regarding the quantity and quality of debt to hold, and decisions regarding how best to balance the various debts to achieve the desired risk / return: investment policy, determining return against risk for individual debts or groups of debt. Debt may also be syndicated, where multiple lenders fund one loan (or multiple loans) to a borrower. Debt portfolios may also be sold to third parties (e.g., at a discount). Debt compliance involves various measures taken to ensure debt repayment. Demonstrating compliance may include documentation of actions taken to repay debt.

[0335] Debt-related transactions (debt transactions) and debt-related actions (debt actions) may include offering debt transactions, underwriting debt transactions, setting interest rates, deferring payment requirements, modifying interest rates, verifying ownership, administering inspections, recording changes in ownership, valuing assets, calling for financing, closing transactions, setting transaction terms, providing required notices, foreclosing on a set of assets, modifying terms, rating entities, syndicating debt, and / or consolidating debt. Debt terms may include, but are not limited to, debt balance, debt principal, fixed interest rate, floating interest rate, payment amounts, payment schedule, balloon payment schedule, identifying assets supporting the notes, identifying fungibility of assets, parties, issuer, purchaser, guarantees, guarantors, collateral, personal guarantees, liens, duration, covenants, foreclosure conditions, default conditions, and consequences of default. While specific examples of debt management and debt management activities are described herein for illustrative purposes, any embodiment having the benefit of the disclosure herein, and any considerations that would be understood by a person of ordinary skill in the art having the benefit of the disclosure herein, is specifically contemplated within the scope of the disclosure.

[0336] As utilized herein, terms, conditions, condition classification, classification model, condition management, and similar terms should be understood broadly. Without being limited to other aspects or descriptions of this disclosure, terms, condition classification, classification model, and condition management include classifying or determining conditions, such as assets, issuers, borrowers, loans, debt, bonds, regulatory status, contractually specified and monitored terms or conditions of a bond, loan, or debt transaction. Based on the classified status of an asset, condition management may include actions to maintain or improve the condition of the asset, or use of the asset as collateral. Based on the classified status, such as the issuer, borrower, or regulatory status of the parties, condition management may include actions to modify the terms of a loan or bond. Condition classification may include various rules, thresholds, condition procedures, workflows, model parameters, etc., for classifying conditions, such as assets, issuers, borrowers, loans, bonds, regulatory status, terms or conditions of bonds, loans or bond transactions, based on data from Internet of Things devices, data from a set of environmental condition sensors, data from a set of social network analytics services, and a set of algorithms for querying network domains, social media data, crowd-sourced data, etc. Classification of conditions may include grouping or labeling entities or clustering entities as similarly positioned with respect to some aspect of the classified condition (e.g., risk, quality, ROI, likelihood of recovery, likelihood of default, or some other aspect of the related debt).

[0337] Various classification models are disclosed where the classification and classification models may be tied to geographic locations associated with collateral, issuers, borrowers, distribution of funds, or other geographic locations. Classification and classification models are disclosed where artificial intelligence is used to improve the classification models (e.g., using artificial intelligence data to make refinements to improve the model). Thus, artificial intelligence is considered as part of the classification model in some examples, and vice versa. Classification and classification models are disclosed where social media data, crowdsourced data, or IoT data is used as input to refine the model or as input to the classification model. Examples of IoT data may include images, sensor data, location data, and the like. Examples of social media data or crowdsourced data may include actions of the parties to a loan, the financial status of the parties, compliance of the parties with the terms and conditions of the loan or bond, and the like. Parties to a loan may include the bond issuer, related entities, lenders, borrowers, and third parties with an interest in the debt. Term management may be discussed in connection with smart contract services including term classification, data collection and monitoring, and transaction management of bonds, loans, and debt. The data collection and monitoring services are also discussed in relation to classifications and classification models associated with bond issuers, assets or secured assets associated with bonds, collateral assets backing bonds, parties to bonds, and the classification of sets thereof. In some embodiments, classification models may be included when discussing bond types. Certain steps, factors, or refinements may be considered part of a classification model. In various embodiments, the classification model may vary in embodiments tied to a particular jurisdiction, or both in the same embodiment. Different classification models may use different data sets (e.g., based on issuers, borrowers, secured assets, bond types, loan types, etc.), and multiple classification models may be used in a single classification. For example, one type of bond, such as municipal bonds, may have a classification model based on bond data from municipalities of similar size and economic prosperity, while another classification model may emphasize data from IoT sensors associated with secured assets.Thus, different classification models offer advantages or risks over other classification models depending on the embodiment and the details of the bond, loan, or debt transaction. A classification model includes an approach or concept for classification. The classified terms for a bond, loan, or debt transaction may include debt principal, debt balance, fixed interest rate, floating interest rate, payment amount, payment schedule, balloon payment schedule, specification of assets backing the bond, loan, or debt transaction, specification of fungibility of assets, party, issuer, purchaser, guarantee, guarantor, collateral, personal guarantee, lien, duration, covenant, mortgage terms, default terms, and / or default consequences. The classified terms may include types of bond issuers such as municipalities, corporations, contractors, government agencies, non-government agencies, non-profit organizations, etc. An entity may include a collection of issuers, a collection of bonds, a collection of parties, and / or a collection of assets. The classified terms may include terms of the entity such as net worth, wealth, debt, location, behavior of the parties (indicative of preferences, behavior indicating debt preferences, behavior, etc.), etc. The classified conditions may include asset or collateral type such as city property, vehicles, vessels, airplanes, buildings, homes, real estate properties, undeveloped land, farms, crops, city facilities, warehouses, inventory, merchandise, securities, currency, tokens of value, tickets, cryptocurrencies, consumables, food, beverages, precious metals, jewelry, gemstones, intellectual property rights, contractual rights, antiques, fixtures, furniture, equipment, tools, machinery, personal property, etc. The classified conditions may include bond type. Bond types include municipal bonds, government bonds, treasury bonds, asset-backed bonds, and corporate bonds. The classified conditions may include default conditions, foreclosure conditions, breach of contract conditions, financial risk conditions, conduct risk conditions, policy risk conditions, financial soundness conditions, physical deficiency conditions, physical soundness conditions, substance risk conditions, and substance soundness conditions. The classified conditions may include an environment selected from among a municipal environment, a corporate environment, a stock trading environment, a real estate environment, a commercial facility, a warehouse facility, a transportation environment, a manufacturing environment, a storage environment, a home, and a vehicle.Actions based on the state of an asset, issuer, borrower, loan, debt, bond, regulatory status, etc. may include managing, reporting, syndicating, consolidating, etc. a series of bonds (municipal bonds, corporate bonds, performance bonds, etc.), monitoring, categorizing, predicting, and otherwise dealing with information such as the reliability, quality, condition, health, financial condition, and physical status of a series of loans (subsidized, unsubsidized, etc.), guarantees, guarantors, collateral backing the guarantees, assets backing the guarantees, etc. Bond transaction activities based on the state of the bond may include offering a debt transaction, underwriting a debt transaction, setting interest rates, deferring payment requirements, fixing interest rates, verifying ownership, administering inspections, recording changes in ownership, assessing the value of assets, calling for loans, closing a transaction, setting terms of a transaction, providing notices required to be served, foreclosing on a series of assets, fixing terms, setting ratings for the entities, syndicating debt, and / or consolidating debt.

[0338] Those skilled in the art, having the benefit of the disclosure herein and generally available knowledge of the envisioned system, can readily determine which aspects of the present disclosure are beneficial to a particular application of the classification models and how to select or combine classification models to arrive at terms and / or calculate the value of collateral given the required data. Specific considerations in selecting appropriate terms that a person skilled in the art, or an embodiment of the present disclosure, would administer include, but are not limited to, the legality of the terms given the jurisdiction of the transaction, the data available for a given collateral, the type of transaction anticipated (loan, bond, or debt), the type of specific collateral, the loan to value ratio, the collateral to loan ratio, the total transaction / loan amount, the credit scores of the borrower and lender, and other considerations. While specific examples of terms, condition classifications, classification models, and condition administration are described herein for illustrative purposes, any embodiment having the benefit of the disclosure herein, and any considerations understood by a person skilled in the art having the benefit of the disclosure herein, are specifically contemplated within the scope of the present disclosure.

[0339] The terms categorize, classify, classify, classify, categorize (and similar terms) utilized herein should be understood broadly. Without being limited to other aspects or descriptions of the present disclosure, categorizing a condition or item may include the act of classifying a condition or item into a group or category based on some aspect, attribute, or characteristic of the condition or item that the condition or item has in common or similar to all items placed in that classification, notwithstanding the divergence of classifications or categories based on other aspects or conditions at that time. Classification may include recognition of one or more parameters, features, characteristics, or phenomena related to the condition or parameters of an item, entity, person, process, item, financial structure, etc. Conditions classified by the condition classification system may include default conditions, foreclosure conditions, covenant violations, financial risk conditions, behavioral risk conditions, contract performance conditions, policy risk conditions, financial health conditions, physical deficiency conditions, physical health conditions, entity risk conditions, and / or entity health conditions. The classification model may automatically classify or categorize items, entities, processes, items, financial structures, etc. based on data received from various sources. A classification model may classify items based on a single attribute or a combination of attributes and may utilize data and models regarding the items being classified. A classification model may classify individual items, entities, financial structures, or groups thereof. Bonds may be classified based on bond type (municipal, corporate, performance bond, etc.), yield, bond rating (a third-party indicator of the bond's quality in terms of the bond issuer's financial strength and / or ability to pay the bond's principal and interest), etc. Lenders or bond issuers may be classified based on the type of lender or issuer, permitted attributes (e.g., income, assets, location (domestic or international), various risk factors, issuer status, etc. Borrowers may be classified based on permitted attributes (e.g., income, assets, total assets, location, credit history), risk factors, current status (e.g., employed, student), party behavior (indicative of preferences, trustworthiness, etc. behavior, etc.), etc.The condition classification system may classify students receiving loans based on the progress of the student toward a degree, the student's grade or rank in a class, the student's status in school (e.g., matriculated, proboscis, etc.), the student's participation in nonprofit activities, the student's deferral status, and the student's participation in public interest activities. Conditions classified by the condition classification system may include the status of the collateral set of the loan and the status of the entity associated with securing the loan. Conditions classified by the condition classification system may include medical conditions of the borrower, guarantor, subsidiaries, etc. Conditions classified by the condition classification system may include compliance with at least one of laws, regulations, and policies associated with the loan transaction and the lending institution. Conditions classified by the condition classification system may include the status of the bond issuer, the condition of the bond, the rating of the loan affiliate, etc. Conditions classified by the state classification system may include the identification of a machine, a part, or an operating mode. Conditions classified by the state classification system may include a state or context (e.g., a state of a machine, a process, a workflow, a marketplace, a storage system, a network, a data collector, etc.). The condition classification system may classify processes that include a state or context (e.g., a data storage process, a network coding process, a network selection process, a data marketplace process, a power generation process, a manufacturing process, a refinancing process, a drilling process, a drilling process, and / or other processes described herein). The condition classification system may classify a set of loan refinancing actions based on predicted outcomes of the set of loan refinancing actions. The condition classification system may classify a set of loans as candidates for consolidation based on attributes such as party identities, interest rates, payment balances, payment terms, payment schedules, loan types, collateral types, party financial status, payment status, collateral status, and collateral value. The condition classification system may classify entities involved in a set such as factored loans, bond issuance activities, mortgage loans, and the like. The condition classification system may classify a set of entities based on predicted outcomes from various loan management activities.The condition classification system may classify a set of issuer conditions based on information from Internet of Things data collection and monitoring services, a set of issuer related parameters, a set of social network monitoring and analysis services, etc. The condition classification system may classify a set of loan collection actions, loan consolidation actions, loan negotiation actions, loan refinancing actions, etc., based on a set of expected outcomes of those activities or entities.

[0340] The terms subsidized loan, subsidized loan (and similar terms) as used herein should be understood broadly. Without being limited to other aspects or explanations of the present disclosure, a subsidized loan is a loan of money or valuable items in which the payment of interest on the value of the loan is deferred, postponed, or delayed, with or without accrual, while the borrower is attending school, unemployed, sick, etc. In an embodiment, a loan may be subsidized if the payment of interest on a portion or subset of the loan is borne or guaranteed by someone other than the borrower. Examples of subsidized loans include municipal subsidized loans, government subsidized loans, student loans, asset-backed subsidized loans, and corporate subsidized loans. Examples of subsidized student loans include government-subsidized student loans that defer or do not accrue interest based on a student's progress toward a degree, a student's participation in non-profit activities, a student's deferral status, and a student's participation in charitable activities. Examples of government-subsidized mortgages include government subsidies that allow borrowers to waive closing costs, first mortgage payments, etc. Such subsidized loan terms may include the location of the property (rural or urban), the borrower's income, the borrower's military status, whether the purchased home can meet health and safety standards, whether there are limitations on the profits that can be made on the sale of the home, etc. Certain uses of the word loan may apply to regular loans rather than subsidized loans. Those skilled in the art, having the benefit of the disclosure herein and knowledge of the contemplated system generally available to them, can read...

Claims

1. a robotic process automation circuit configured to interpret information from a plurality of data sources and interface with a plurality of management applications; each of the plurality of management applications is associated with a different one of the plurality of financial institutions; the robotic process automation circuitry further comprising artificial intelligence circuitry configured to improve a process of at least one of the plurality of management applications in response to information from the plurality of data sources.

2. 10. The system of claim 1, wherein the artificial intelligence circuitry further comprises at least one circuitry selected from the group consisting of a smart contract service circuitry, an evaluation circuitry, and an automated agent circuitry.

3. 2. The system of claim 1, wherein the plurality of management applications includes at least two applications selected from applications including an investment application, an asset management application, a lending application, a risk management application, a marketing application, a trading application, a tax application, a fraud application, a financial services application, a security application, an underwriting application, a blockchain application, a real estate application, a regulatory application, a platform marketplace application, an assurance application, an analytics application, a pricing application, and a smart contract application.

4. 2. The system of claim 1, wherein the plurality of data sources includes at least two applications selected from applications including an access data source, an asset / facility data source, a worker data source, a claims data source, an accounting data source, an event data source, and an underwriting data source.

5. 2. The system of claim 1, wherein the plurality of management applications includes a real estate application, and the robotic process automation circuitry is further configured to automate an inspection process for a real estate property.

6. 6. The system of claim 5, wherein the robotic process automation circuitry is further configured to automate a real estate inspection process by performing at least one operation selected from the group consisting of providing either video inspection commands or camera inspection commands, scheduling inspection events utilizing data from a plurality of data sources, determining inspection criteria in response to the plurality of inspection data and inspection results, and providing inspection commands in response to the plurality of inspection data and inspection results.

7. 7. The system of claim 6, wherein the robotic process automation circuitry is further configured to automate the real estate inspection process in response to at least one data source of the plurality of data sources being inaccessible to the real estate application.

8. 2. The system of claim 1, wherein at least one of the plurality of data sources is inaccessible to each of at least one of the plurality of management applications having an improved process by the robotic automation circuitry.

9. 10. The system of claim 8, wherein at least one of the plurality of management applications whose processes are improved by the robotic automation circuitry comprises a real estate application, and at least one of the plurality of data sources comprises at least one data source selected from data sources including a claims data source, a pricing data source, an asset and equipment data source, a worker data source, and an event data source.

10. 9. The system of claim 8, wherein at least one of the plurality of management applications having processes improved by the robotic automation circuitry comprises an asset management application, and at least one of the plurality of data sources includes at least one data source selected from data sources including an access data source, a price data source, an accounting data source, a worker data source, and an event data source.

11. 9. The system of claim 8, wherein at least one of the plurality of management applications having processes improved by the robotic automation circuitry includes a loan management application, and at least one of the plurality of data sources includes at least one data source selected from data sources including an asset and facility data source, a claims data source, a worker data source, and an event data source.

12. 9. The system of claim 8, wherein at least one of the plurality of management applications whose processes are improved by the robotic automation circuitry comprises a marketing management application, and wherein at least one of the plurality of data sources comprises at least one data source selected from data sources including an asset / facility data source, a claims data source, a worker data source, an event data source, and an underwriting data source.

13. 9. The system of claim 8, wherein at least one of the plurality of management applications having processes improved by the robotic automation circuitry includes a transaction management application, and at least one of the plurality of data sources includes at least one data source selected from data sources including an asset and facility data source, a claims data source, a worker data source, and an event data source.

14. 9. The system of claim 8, wherein at least one of the plurality of management applications having processes improved by the robotic automation circuitry includes an analytics management application, and at least one of the plurality of data sources includes at least one data source selected from data sources including an access data source, a claims data source, a worker data source, and an event data source.

15. 10. The system of claim 1, wherein the robotic process automation circuitry is further configured to improve a process of at least one of the plurality of management applications by providing an output to at least one entity selected from the following entities: an external market, a banking facility, an insurance facility, a financial services facility, an operations facility, a collaborative robot facility, a worker, a wearable device, an external process, and a machine.

16. 16. The system of claim 15, wherein the robotic process automation circuitry is further configured to interpret results from the at least one entity, and wherein the artificial intelligence circuitry is further configured to iteratively improve the process in response to the results from the at least one entity.

17. includes robotic process automation circuitry that interprets information from multiple data sources and interfaces with multiple control applications; each of the plurality of management applications is associated with a different one of the plurality of financial institutions; the robotic process automation circuit further comprises an opportunity miner component configured to determine process improvement opportunities for at least one of the plurality of management applications in response to information from the plurality of data sources; The system provides an output to at least one entity associated with the process improvement opportunity in response to the determined process improvement opportunity.

18. 20. The system of claim 17, wherein the plurality of management applications includes at least two applications selected from the following applications: an investment application, an asset management application, a lending application, a risk management application, a marketing application, a trading application, a tax application, a fraud application, a financial services application, a security application, an underwriting application, a blockchain application, a real estate application, a regulatory application, a platform marketplace application, an assurance application, an analytics application, a pricing application, and a smart contract application.

19. 20. The system of claim 17, wherein the plurality of data sources includes at least two applications selected from applications including an access data source, an asset and facility data source, a worker data source, a claims data source, an accounting data source, an event data source, and an underwriting data source.

20. 20. The system of claim 17, wherein the at least one entity comprises an entity selected from the following entities: an external market, a banking facility, an insurance facility, a financial services facility, an operating facility, a collaborative robot facility, a worker, a wearable device, an external process, and a machine.

21. 20. The system of claim 17, wherein the opportunity miner component is further configured to: determine a plurality of process improvement opportunities for one of the plurality of management applications in response to information from the plurality of data sources; and provide one of a prioritized list or visualization of the plurality of process improvement opportunities for one of the plurality of management applications.

22. 20. The system of claim 17, wherein the opportunity miner component is further configured to determine process improvement opportunities in response to at least one parameter selected from parameters including a time savings value, a cost savings value, and an improved outcome value.

23. 20. The system of claim 17, wherein the opportunity miner component is further configured to determine process improvement opportunities in response to the value translation from the value translation application.

24. 20. The system of claim 17, wherein the plurality of management applications includes trading applications, and the robotic process automation circuitry is further configured to automate a trading service process.

25. 25. The system of claim 24, wherein the robotic process automation circuitry is further configured to automate a trading servicing process by performing at least one operation selected from the operations including: scheduling a trading event utilizing data from a plurality of data sources; determining trading criteria in response to the plurality of asset data and trading results; and providing trading commands in response to the plurality of asset data and trading results.

26. 26. The system of claim 25, wherein the robotic process automation circuitry is further configured to automate a trading servicing process in response to at least one of a plurality of data sources that is inaccessible to the trading application.

27. 20. The system of claim 17, wherein the robotic process automation circuitry is further configured to improve a process of at least one of the plurality of management applications by providing an output to at least one entity selected from the following entities: an external market, a banking facility, an insurance facility, a financial services facility, an operations facility, a collaborative robot facility, a worker, a wearable device, an external process, and a machine.

28. 30. The system of claim 27, wherein the robotic process automation circuitry is further configured to interpret results from the at least one entity, and the opportunity miner component is further configured to iteratively improve the process in response to the results from the at least one entity.

29. 20. The system of claim 17, wherein at least one of the plurality of data sources is inaccessible to each of at least one of the plurality of management applications having an improved process by the robotic automation circuitry.

30. 30. The system of claim 29, wherein at least one of the plurality of management applications having processes improved by the robotic automation circuitry includes a tax application, and at least one of the plurality of data sources includes at least one data source selected from data sources including a claims data source, a pricing data source, an asset and facilities data source, a worker data source, and an event data source.

31. 30. The system of claim 29, wherein at least one of the plurality of management applications having processes improved by the robotic automation circuitry includes an asset management application, and at least one of the plurality of data sources includes at least one data source selected from data sources including an access data source, a pricing data source, an accounting data source, a worker data source, and an event data source.

32. 30. The system of claim 29, wherein at least one of the plurality of management applications having processes improved by the robotic automation circuitry includes a loan management application, and at least one of the plurality of data sources includes at least one data source selected from the following data sources: an asset and facilities data source, a claims data source, a worker data source, and an event data source.

33. 30. The system of claim 29, wherein at least one of the plurality of management applications having processes improved by the robotic automation circuitry includes a marketing management application, and at least one of the plurality of data sources includes at least one data source selected from data sources including an asset and facility data source, a claims data source, a worker data source, an event data source, and an underwriting data source.

34. 30. The system of claim 29, wherein at least one of the plurality of management applications having processes improved by the robotic automation circuitry includes an investment management application, and at least one of the plurality of data sources includes at least one data source selected from data sources including an asset and facility data source, a claims data source, a worker data source, and an event data source.

35. 30. The system of claim 29, wherein at least one of the plurality of management applications having processes improved by the robotic automation circuitry includes an underwriting management application, and at least one of the plurality of data sources includes at least one data source selected from the following data sources: an access data source, a claims data source, a worker data source, and an event data source.

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