Marketplace Orchestration System for Facilitating Electronic Market Transactions

Abstract

A system and method for configuring and launching a marketplace is disclosed. The method may include identifying a new marketplace opportunity, receiving marketplace opportunity data, determining configuration parameters, and determining the feasibility of implementing the new marketplace configuration. The architecture of the new marketplace may be determined and marketplace objects may be configured. Data resources and their configuration in a model may be determined and the data resources may be connected to the marketplace objects. The new marketplace may then be launched.

Description

[Technical Field]

[0001] (CROSS-REFERENCE TO RELATED APPLICATIONS) This application claims the benefit of priority to PCT Application No. PCT / US2021 / 042050 (Attorney Docket No. SFTX-0018-WO), filed July 16, 2021, and entitled "SYSTEMS AND METHODS FOR CONTROLLING RIGHTSRATED TO DIGITAL KNOWLEDGE."

[0002] This application claims the benefit of priority to U.S. Provisional Patent Application No. 63 / 127,980, entitled "MARKET ORCHESTRATION SYSTEM FOR FACILITATING ELECTRONIC MARKETPLACE TRANSACTIONS," filed on December 18, 2020 (Attorney Docket No. SFTX-0016-P01), U.S. Provisional Patent Application No. 63 / 137,690, entitled "METHODS AND SYSTEMS FOR MANAGEMENT OF DIGITAL KNOWLEDGE," filed on July 14, 2021 (Attorney Docket No. SFTX-0019-P02), and U.S. Provisional Patent Application No. 63 / 221,903, entitled "METHODS AND SYSTEMS FOR MANAGEMENT OF DIGITAL KNOWLEDGE," filed on July 14, 2021 (Attorney Docket No. SFTX-0019-P02).

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

[0004] (background) Exchanges and other marketplaces provide various important functions to their stakeholders, including the ability to find counterparties willing to engage in transactions involving a wide range of asset classes. Among other things, exchange trading allows parties to secure liquidity, execute financial strategies (such as arbitrage trading), manage risk (through options and futures contracts), aggregate capital, transform value from one asset class to another, participate in trading profits, influence behavior, and gain insights (through data streams about trading). Successful marketplaces like the New York Stock Exchange (NYSE) and the Chicago Mercantile Exchange (CME) are fundamental components of the global economy, and new exchanges regularly emerge to serve new categories. Exchanges increasingly rely on information technology infrastructure capabilities for a wide range of core functions for trading, presentation, execution, reporting, analysis, settlement, and other functions, including distributed storage, caching, high-speed networking, algorithmic trading, big data, data integration, modeling and analytics, robotic process automation, distributed ledger technology (DLT), smart contracts, real-time data collection, search, asset digitization, and more. There is a need in the art to provide intelligent orchestration of markets for a broad and expanding range of asset classes and to engage an increasingly diverse range of stakeholders.

[0005] There is a huge amount of information exchanged digitally, and the volume continues to grow daily. This information can include valuable and confidential information, such as trade secrets, know-how, patented materials, and copyrighted works. Some of this information is subject to restrictions on the ability to view, edit, modify, use, transmit, sell, purchase, rent, review, license, or source the digital information (e.g., restrictions on patent licenses, trademark licenses, contracts, and copyright licenses). Setting and enforcing access and control restrictions is difficult, and computer-based systems for doing so have potential flaws, including the risk of fraud and unreliability on the part of the system owner or maintainer, and the risk that others may gain unauthorized access and copy, edit, or otherwise tamper with digital knowledge. Thus, there is a need for a cryptographically secure blockchain for knowledge systems that can store digital knowledge and provide convenient and secure control of it.

[0006] Lending transactions provide funds for a variety of needs, such as housing, education, businesses, and government projects, and allow lenders to earn financial returns. However, lending transactions are fraught with many problems, including information opacity and asymmetry, moral hazard due to the shifting of risks and the consequences of inappropriate behavior, complex application and negotiation processes, burdensome regulatory and policy regimes, difficulty in determining the value of assets that serve as collateral or backing for debt, and difficulty in determining the trustworthiness and financial soundness of entities.

[0007] Machines and automated agents are increasingly involved in market activities, including data collection, forecasting, planning, and trade execution. This includes sophisticated systems such as those used for high-speed trading. Methods and systems are needed to improve the machines that enable these markets, increasing their efficiency, speed, and reliability for participants in these markets.

[0008] Many markets are becoming more decentralized rather than centralized, with distributed ledgers like blockchain, peer-to-peer exchange models, and microtransactions replacing or complementing traditional models with centralized authorities and intermediaries. This calls for improved machines that allow decentralized transactions to occur at scale between many participants, including human participants and automated agents.

[0009] As the chain of blocks on blockchains, such as cryptocurrencies, grows, energy-intensive computations, such as calculating very large hash functions, are required. In systems using proof-of-work or proof-of-stake, "mining" is a massive application of computer processing power to perform the calculations that underpin collective trust in transactions recorded on the blockchain.

[0010] Many applications of artificial intelligence also require energy-intensive computation, such as when very large neural networks with a large number of interconnections operate on many inputs to produce one or more outputs, such as predictions, classifications, optimizations or control outputs.

[0011] Additionally, the development of the Internet of Things and cloud computing platforms has led to a rapid increase in devices, applications, and the connections between them, and data centers housing IT components such as servers now account for a significant proportion of energy consumption in developed countries, including the United States.

[0012] As a result, energy consumption has become a major factor in the use of computing resources, and energy resources and computing resources (or simply "energy and computing") are beginning to converge in various ways, such as requesting, purchasing, providing, configuring, and managing inputs, activities, and outputs. For example, projects are underway to place large-scale computing resource facilities, such as those for cryptocurrency mining such as Bitcoin, in close proximity to large hydroelectric power plants such as Niagara Falls.

[0013] A significant 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 network resources (e.g., as network performance fluctuates), volatility and uncertainty in the various end markets to which energy and computing resources are applied (e.g., volatility of cryptocurrencies, volatility in energy markets, volatility of prices in various other markets, uncertainty about the usefulness of artificial intelligence in a wide range of applications), and other factors. Summary of the Invention

[0014] (overview) Provided herein are methods, systems, and other elements (optionally configured as a platform) for intelligent and automated orchestration of marketplaces, applicable in various embodiments to a wide range of asset classes involving various stakeholders. Marketplace orchestration enables the identification, configuration, and execution of a wide range of market types in which goods, services, or other items or assets are exchanged. These marketplaces can support traditional asset classes (e.g., stocks, commodities, bonds) and non-traditional asset classes (e.g., human-provided services and entertainment experiences). While traditional markets operate with a consistent set of assets established over time, market orchestration enables the configuration and execution of a wide variety of marketplaces with customizable parameters, bringing much-needed flexibility to trading.

[0015] An aspect of the disclosure relates to a method for configuring and launching a marketplace. The method may include identifying, by a processing system, opportunities to promote a new marketplace. The method may include receiving, by a processing system, marketplace opportunity data. The marketplace opportunity data may include information related to one or more assets. The method may include determining, by the processing system, configuration parameters to be implemented in the new marketplace. The method may include determining, by the processing system, feasibility of implementing the configuration parameters in the new marketplace. The method may include determining, by the processing system, a database to support the new marketplace. The method may include determining, by the processing system, an architecture for the new marketplace. The method may include determining, by the processing system, a design of data within the selected database environment. The method may include configuring, by the processing system, marketplace objects. The method may include connecting, by the processing system, the new marketplace.

[0016] Another aspect of the present disclosure relates to a method for configuring a role-based market orchestration digital twin. The method may include generating, by a processing system, a digital twin of a marketplace. The digital twin may be a digital representation of the structure of the market. The method may include determining, by the processing system, a set of relationships between different roles in a set of roles based on the marketplace. The method may include determining, by the processing system, a set of settings for roles from the set of roles based on the inferred relationships. The method may include providing a set of settings for the set of roles using the inferred relationships in the marketplace structure. The method may include linking a set of identities to the roles. The method may include determining, by the processing system, a presentation layer configuration of the role-based market orchestration digital twin corresponding to the roles based on the settings of at least one role linked to the identities. The presentation layer configuration system may define a set of states to be depicted in the role-based market orchestration digital twin associated with the roles. The method may include determining, by the processing system, a set of data sources providing data corresponding to the set of states. Each data source may provide one or more respective types of data. The method may include configuring one or more data structures to store data received from the one or more data sources. The one or more data structures may be configured to provide data used to populate one or more of the sets of states of the role-based marketplace orchestration digital twin. The method may include linking a set of identities to a set of roles. In an embodiment, each identity may correspond to a respective role from the set of roles.In embodiments, the role-based market orchestration digital twin may be integrated with a market orchestration platform operating on the role-based market orchestration digital twin such that changes in the market orchestration platform are automatically reflected in the role-based market orchestration digital twin. In embodiments, the set of settings for the set of roles includes role-based permission settings. In embodiments, the set of settings for the set of roles includes role-based preference settings. In embodiments, the role-based preference settings are configured based on a set of role-specific templates. In embodiments, the set of templates includes at least one of a trader template, a marketplace host template, a broker template, a buyer template, and a seller template. In embodiments, the set of settings for the set of roles includes role-based taxonomy settings. In embodiments, the taxonomy settings specify taxonomies used to characterize data presented in the role-based digital twin such that the data is presented in taxonomies linked to corresponding roles in the role-based digital twin. In embodiments, the set of taxonomies includes at least one of a trader template, a marketplace host template, a broker template, a buyer template, and a seller template. In embodiments, the at least one role is selected from among a trader role, a marketplace host role, a broker role, a buyer role, and a seller role. In embodiments, the at least one role is selected from among a market maker role, a market analyst role, an exchange administrator role, a broker-dealer role, a trading role, a settlement role, a contract counterparty role, an exchange rate setting role, a marketplace orchestration role, a market configuration role, and a contract configuration role.In an embodiment, the role is selected from a chief marketing officer role, a product development role, a supply chain manager role, a customer role, a supplier role, a vendor role, a demand management role, a marketing manager role, a sales manager role, a service manager role, a demand forecasting role, a retail manager role, a warehouse manager role, a sales associate role, and a distribution center manager role.

[0017] Another aspect of the invention relates to a method for configuring an intelligent agent. The method may include receiving digital twin data from a set of data sources. The digital data may include sensor data received from a set of sensors monitoring a set of monitored physical entities associated with a marketplace, the sensor data being transported by a set of network entities. The digital data may include a marketplace data stream generated by a set of marketplace assets, the marketplace assets including at least one of physical entities associated with the marketplace and digital entities associated with the marketplace. The method may include structuring the digital twin data into a set of digital twin data structures configured to provide a plurality of different role-based digital twins. The method may include receiving a request for a role-based digital twin from a client application. In an embodiment, the role-based digital twins are configured with respect to defined roles within the marketplace. The method may include determining a subset of structured digital twin data corresponding to a set of states to be depicted in the role-based digital twin. The method may include providing the subset of structured digital twin data to the client application. The method may include receiving intelligent agent training datasets from the client application, each intelligent agent training dataset indicating a respective action taken by a user using the client application and one or more features corresponding to the respective action. The method may include training an intelligent agent on behalf of the user based on the intelligent agent training dataset. In embodiments, the intelligent agent is configured to determine an action to be performed on behalf of the user. In embodiments, the determined action is recommended to the user or automatically performed on behalf of the user.In embodiments, the role is selected from a trader role, a marketplace host role, a broker role, a buyer role, and a seller role. In embodiments, the role is selected from a market maker role, an exchange administrator role, a broker-dealer role, a trading role, a settlement role, a counterparty role, an exchange rate setting role, a marketplace orchestration role, a market setting role, and a contract setting role. In embodiments, the role is selected from a chief marketing officer role, a product development role, a supply chain manager role, a customer role, a supplier role, a vendor role, a demand management role, a marketing manager role, a sales manager role, a service manager role, a demand forecasting role, a retail manager role, a warehouse manager role, a salesperson role, and a distribution center manager role. In embodiments, the intelligent agent training data includes interaction training data indicative of a set of interactions by a user with a set of experts during the performance of a role. In embodiments, the set of interactions used to train the intelligent agent includes user interactions with a physical entity. In embodiments, the set of interactions used to train the intelligent agent includes user interactions with a role-based digital twin. In embodiments, the set of interactions used to train the intelligent agent includes user interactions with sensor data depicted in the role-based digital twin. In embodiments, the set of interactions used to train the artificial intelligence system includes expert interactions with data streams generated by physical entities. In embodiments, the set of interactions used to train the intelligent agent system includes expert interactions with one or more computational entities. In embodiments, the set of interactions used to train the intelligent agent includes user interactions with one or more network entities.In embodiments, the intelligent agent is trained to determine actions selected from the group consisting of: selecting an asset, pricing the asset, configuring a marketplace, listing an asset on a marketplace, uploading information related to an asset listed on the marketplace, identifying a trading partner, selecting a trading partner, identifying an opportunity, selecting an opportunity, conducting negotiations, identifying a need for a new marketplace, digitally inspecting the asset, physically inspecting the asset, configuring a digital twin, placing an order request, generating a smart contract, physically delivering the asset, physically retrieving the asset, selecting a trading strategy, brokering the transaction, valuing the asset, and performing order matching. In embodiments, the intelligent agent is trained on a training set of outcomes resulting from actions taken by a user. In embodiments, the training set of outcomes includes data regarding at least one of financial outcomes, operational outcomes, failure outcomes, success outcomes, performance indicator outcomes, output outcomes, consumption outcomes, energy utilization outcomes, resource utilization outcomes, cost outcomes, profit outcomes, revenue outcomes, sales outcomes, and production outcomes.In an embodiment, the intelligent agent is trained to perform actions selected from determining the system architecture, reporting on a state, reporting on an event, reporting on a context, reporting on a condition, determining a model, configuring a model, populating a model, designing a system, designing a process, designing a device, engineering a system, engineering a device, engineering a process, engineering a product, maintaining a system, maintaining a device, maintaining a process, maintaining a network, maintaining computing resources, maintaining a device, maintaining hardware, repairing a system, repairing a device, repairing a process, repairing a network, repairing computing resources, repairing a device, repairing hardware, assembling a system, assembling a device, assembling a process, assembling a network, assembling computing resources, assembling a device, assembling a software, determining a price, physically fixing a system. physically securing devices, physically secure systems, physically secure devices, physically secure networks, physically secure computing resources, physically secure equipment, physically secure hardware, cybersecurity systems, cybersecurity devices, processes, cybersecurity networks, cybersecurity computing resources, cybersecurity equipment, cybersecurity hardware, threat detection, fault detection, system tuning, device tuning, process tuning, network tuning, computing resource tuning, equipment tuning, hardware tuning, system optimization, device optimization, process optimization, network optimization, computing resource optimization, equipment optimization, hardware optimization, system monitoring, device monitoring, process monitoring, network monitoring, computing resource monitoring, equipment monitoring, hardware monitoring, system configuration, device configuration, process configuration, network configuration, computing resource configuration, equipment configuration, and hardware configuration.In embodiments, the intelligent agent is trained and / or configured via feedback from at least one expert in a defined role regarding a set of outputs of the intelligent agent. In embodiments, the set of outputs of the intelligent agent for which the expert provides feedback includes at least one of recommendation, classification, prediction, control instruction, input selection, protocol selection, communication, alert, communication target selection, data storage selection, computation selection, configuration, event detection, and prediction. In embodiments, the feedback of the at least one expert is solicited to train the intelligent agent to replicate the expert's expertise in the role. In embodiments, the feedback of the at least one expert is used to modify the set of inputs to the intelligent agent. In embodiments, the feedback of the at least one expert is used to identify and characterize at least one error by the intelligent agent. In embodiments, a report regarding the set of errors is provided to a user of the intelligent agent to enable reconfiguration of the intelligent agent based on the feedback from the expert. In embodiments, the artificial intelligence system includes at least one of removing inputs that cause errors, reconfiguring a set of nodes in the artificial intelligence system, reconfiguring a set of weights in the artificial intelligence system, reconfiguring a set of outputs of the artificial intelligence system, reconfiguring a process flow within the artificial intelligence system, and augmenting a set of inputs to the artificial intelligence system. In embodiments, the intelligent agent is trained based on a training set of outcomes to provide training and / or guidance to individuals fulfilling defined roles in the market. In embodiments, the training set of outcomes includes data related to at least one of financial outcomes, operational outcomes, failure outcomes, success outcomes, performance indicator outcomes, output outcomes, consumption outcomes, energy utilization outcomes, resource utilization outcomes, cost outcomes, profit outcomes, revenue outcomes, sales outcomes, and production outcomes.In an embodiment, the method further includes analyzing the training dataset of interactions to identify types of processing performed by the user when analyzing the set of interactions, in an embodiment, the types of processing are selected from the set of audio processing, tactile processing, textual processing, motor processing, visual processing, spatiotemporal processing, mathematical processing, and analytical processing when analyzing audio information.

[0018] Another aspect of the present disclosure relates to a method for rewarding expert workers. The method may include adopting an information technology architecture that supports a digital twin of a set of physical entities. In an embodiment, the information technology architecture includes: a set of sensors providing sensor data regarding the set of physical entities; a set of data streams generated by at least a subset of the set of physical entities; a set of computational entities for processing the data; a set of network entities for transporting data obtained from the set of sensors and the set of data streams; and a set of data processing systems for extracting the data. The method may include transforming and loading the data transported by the network entities into a set of resources that are sources of the digital twin. The method may include integrating an artificial intelligence system with the information technology architecture, the artificial intelligence system configured to operate as a double of the expert worker for a defined role in a market. In an embodiment, the expert worker is provided a benefit for training the artificial intelligence system. In an embodiment, the benefit is a reward based on the results of use of the artificial intelligence system. In an embodiment, the reward is a reward based on the productivity of the artificial intelligence system. In an embodiment, the benefit is a reward based on a measure of the expertise of the artificial intelligence system. In an embodiment, the reward is a share of revenue or profits generated by the work of the artificial intelligence system. In an embodiment, the reward is managed via a smart contract operating on a blockchain. In embodiments, the artificial intelligence system is trained based on a training set of data comprising a set of interactions by a particular expert worker during the performance of a defined role. In embodiments, the set of interactions used to train the artificial intelligence system comprises interactions of the expert with a physical entity. In embodiments, the set of interactions used to train the artificial intelligence system comprises interactions of the expert with a digital twin. In embodiments, the set of interactions used to train the artificial intelligence system comprises interactions of the expert with sensor data.In embodiments, the set of interactions used to train the artificial intelligence system includes expert interactions with data streams generated by physical entities. In embodiments, the set of interactions used to train the artificial intelligence system includes interactions between an expert and a computational entity. In embodiments, the set of interactions used to train the artificial intelligence system includes expert interactions with network entities. In embodiments, the artificial intelligence system is trained based on the interactions to determine an action selected from the group consisting of asset selection, asset pricing, marketplace configuration, listing an asset on a marketplace, uploading information related to an asset listed on a marketplace, identifying a counterparty, selecting a counterparty, identifying an opportunity, opportunity selection, conducting negotiations, identifying a need for a new marketplace, digitally inspecting the asset, physically inspecting the asset, configuring a digital twin, placing an order request, generating a smart contract, physically delivering the asset, physically retrieving the asset, selecting a trading strategy, brokering the trade, valuing the asset, and matching the order. In embodiments, the training set of interactions is analyzed to identify chains of inferences of the expert worker based on a set of information, and the chains of inferences are embodied in the configuration of the artificial intelligence system. In an embodiment, the chain of inferences is analyzed to identify the type of inference of the expert worker, and the type of inferences is used as a basis for constructing an artificial intelligence system. In an embodiment, the chain of inferences is a deductive chain of inferences from a set of data.In an embodiment, the artificial intelligence system performs tasks such as determining the system architecture, reporting on status, reporting on events, reporting on context, reporting on conditions, determining a model, configuring a model, inputting a model, designing a system, designing a process, designing a device, engineering a system, engineering a device, engineering a process, engineering a product, maintaining a system, maintaining a device, maintaining a process, maintaining a system, maintaining a device, maintaining a process, maintaining a network, maintaining computing resources, maintaining a device, maintaining hardware, repairing a system, repairing a device, repairing a process, repairing a network, repairing computing resources, repairing a device, repairing hardware, assembling a system, assembling a device, assembling a process, assembling a network, assembling computing resources, assembling a device, assembling a software, determining a price, The cybersecurity expert is trained to perform operations selected from the following: physically secure a system, physically secure a device, physically secure a system, physically secure a device, physically secure a network, physically secure computing resources, physically secure equipment, physically secure hardware, cybersecurity system, cybersecurity device, process, cybersecurity network, cybersecurity computing resources, cybersecurity equipment, cybersecurity hardware, threat detection, fault detection, system tuning, device tuning, process tuning, network tuning, computing resource tuning, equipment tuning, system optimization, device optimization, process optimization, network optimization, computing resource optimization, equipment optimization, hardware optimization, system monitoring, device monitoring, process monitoring, network monitoring, computing resource monitoring, equipment monitoring, hardware monitoring, system configuration, device configuration, process configuration, network configuration, computing resource configuration, equipment configuration, and hardware configuration.

[0019] Another aspect of the present disclosure relates to a method for integrating an AI embodied workforce double into a digital twin data processing architecture. The method may include adopting an information technology architecture that supports a digital twin of a set of physical entities. In an embodiment, the architecture includes: a set of sensors providing sensor data about the set of physical entities; a set of data streams generated by at least a subset of the set of physical entities; a set of computational entities for processing the data; a set of network entities for transporting data obtained from the set of sensors and the set of data streams; and a set of data processing systems that extract, transform, and load the data transported by the network entities into resources of a set that is a resource of the digital twin. The method may include integrating an artificial intelligence system with the information technology architecture. In an embodiment, the artificial intelligence system is configured to operate as a double of a defined marketplace orchestration workforce that includes a set of defined marketplace roles. In an embodiment, the artificial intelligence system is trained based on a training set of data that includes a set of interactions by members of the defined workforce while performing the set of defined roles. In an embodiment, the set of interactions used to train the artificial intelligence system includes interactions of the workforce with a physical entity. In an embodiment, the set of interactions used to train the artificial intelligence system includes interactions of the workforce with the digital twin. In embodiments, the set of interactions used to train the artificial intelligence system includes workforce interactions with sensor data. In embodiments, the set of interactions used to train the artificial intelligence system includes workforce interactions with data streams generated by physical entities. In embodiments, the set of interactions used to train the artificial intelligence system includes workforce interactions with computational entities.In embodiments, the set of interactions used to train the artificial intelligence system includes workforce interactions with network entities. In embodiments, the training set of interactions is analyzed to identify a chain of worker actions based on a set of information, and the chain of inference is embodied in the configuration of the artificial intelligence system. In embodiments, the training set of interactions is analyzed to identify a type of workforce action for the set of information, and the type of action is embodied in the configuration of the artificial intelligence system. In embodiments, the artificial intelligence system is trained based on the interactions to determine an action selected from the group consisting of asset selection, asset pricing, marketplace configuration, listing an asset on a marketplace, uploading information related to an asset listed on a marketplace, counterparty identification, counterparty selection, opportunity identification, opportunity selection, conducting negotiations, identifying the need for a new marketplace, digitally inspecting the asset, physically inspecting the asset, configuring a digital twin, order submission, smart contract generation, physical asset delivery, physical asset recovery, trading strategy selection, brokering the trade, asset valuation, and order matching. In embodiments, the artificial intelligence system is trained on the training set of results. In embodiments, the training set of outcomes includes data regarding at least one of financial outcomes, operational outcomes, failure outcomes, success outcomes, performance indicator outcomes, output outcomes, consumption outcomes, energy utilization outcomes, resource utilization outcomes, cost outcomes, profit outcomes, revenue outcomes, sales outcomes, and production outcomes. In embodiments, the artificial intelligence system is trained and / or configured via feedback from members of the workforce regarding the set of outputs of the artificial intelligence system. In embodiments, the set of outputs of the artificial intelligence system for which workforce members provide feedback includes at least one of recommendation, classification, prediction, control instruction, input selection, protocol selection, communication, alert, communication target selection, data storage selection, computation selection, configuration, event detection, and prediction. In embodiments, workforce member feedback is solicited to train the artificial intelligence system to replicate the behavior of the workforce in a defined set of roles.In embodiments, workforce member feedback is used to modify a set of inputs to the artificial intelligence system. In embodiments, workforce member feedback is used to identify and characterize at least one error by the artificial intelligence system. In embodiments, a report on the set of errors is provided to a manager of the artificial intelligence system to enable reconfiguration of the artificial intelligence system based on the feedback. In embodiments, reconfiguring the artificial intelligence system includes at least one of removing the input that caused the error, reconfiguring a set of nodes in the artificial intelligence system, reconfiguring a set of weights in the artificial intelligence system, reconfiguring a set of outputs of the artificial intelligence system, reconfiguring a process flow within the artificial intelligence system, and augmenting a set of inputs to the artificial intelligence system. In embodiments, the artificial intelligence system is configured to provide at least one of training and guidance to other workers to enable them to perform roles within the set of defined worker roles. In embodiments, the artificial intelligence system learns from a training set of outcomes to enhance the training and guidance. In embodiments, the training set of outcomes includes data regarding at least one of financial outcomes, operational outcomes, failure outcomes, success outcomes, performance indicator outcomes, output outcomes, consumption outcomes, energy utilization outcomes, resource utilization outcomes, cost outcomes, profit outcomes, revenue outcomes, sales outcomes, and production outcomes.In an embodiment, the artificial intelligence system is trained to perform an action selected from determining the system architecture, reporting on a state, reporting on an event, reporting on a context, reporting on a condition, determining a model, configuring a model, populating a model, designing a system, designing a process, designing an equipment, engineering a system, engineering an equipment, engineering a process, engineering a product, maintaining a system, maintaining an equipment, maintaining a process, maintaining a network, maintaining computing resources, maintaining an equipment, maintaining hardware, repairing a system, repairing an equipment, repairing a process, repairing a network, repairing computing resources, repairing an equipment, repairing hardware, assembling a system, assembling an equipment, assembling a process, assembling a network, assembling computing resources, assembling an equipment, assembling software, determining a price, physically fixing a system, and assembling a device. physically securing a device, physically secure system, physically secure device, physically secure network, physically secure computing resources, physically secure equipment, physically secure hardware, cybersecurity system, cybersecurity device, process, cybersecurity network, cybersecurity computing resources, cybersecurity equipment, cybersecurity hardware, threat detection, fault detection, system tuning, device tuning, process tuning, network tuning, computing resource tuning, equipment tuning hardware tuning, system optimization, device optimization, process optimization, network optimization, computing resource optimization, equipment optimization, hardware optimization, system monitoring, device monitoring, process monitoring, network monitoring, computing resource monitoring, equipment monitoring, hardware monitoring, system configuration, device configuration, process configuration, network configuration, computing resource configuration, equipment configuration, and hardware configuration. In an embodiment, the artificial intelligence system is configured to provide at least one of training and guidance to the worker to enable the worker to perform the defined role.In embodiments, the artificial intelligence system learns from a training set of outcomes to enhance training and guidance. In embodiments, the training set of outcomes includes data regarding at least one of financial outcomes, operational outcomes, failure outcomes, success outcomes, performance indicator outcomes, output outcomes, consumption outcomes, energy utilization outcomes, resource utilization outcomes, cost outcomes, profit outcomes, revenue outcomes, sales outcomes, and production outcomes. In embodiments, outcomes are compared between a set of worker actions and a set of outputs of the artificial intelligence system. In embodiments, the comparison is used to train workers. In embodiments, the comparison is used to improve the artificial intelligence system. In embodiments, at least one role in the set of workforce roles is selected from a trader role, a marketplace host role, a broker role, a buyer role, and a seller role. In embodiments, the workforce is a supply chain management workforce. In embodiments, the workforce is a demand planning workforce. In embodiments, the workforce is a logistics planning workforce. In embodiments, the workforce is a vendor management workforce. In embodiments, the workforce is a marketplace intermediary workforce. In embodiments, the workforce is a trading workforce for the marketplace. In embodiments, the workforce is a trade coordination workforce for the marketplace. In embodiments, the workforce is a trade execution workforce for the marketplace. In embodiments, the computational entity and the network entity are integrated as a converged computational and network entity.

[0020] Another aspect of the invention relates to a method for constructing a workforce digital twin. The method can include representing an organizational structure of an enterprise in a digital twin of a digital marketplace orchestration enterprise. The method can include analyzing the structure to infer relationships between a set of roles within the organizational structure, where the relationships and roles can define a workforce of the digital marketplace orchestration enterprise. The method can include constructing a presentation layer of the digital twin to represent the digital marketplace orchestration enterprise as a set of workforces having a set of attributes and relationships. In embodiments, the digital twin integrates with a marketplace orchestration platform that operates on a data structure representing the set of roles in the marketplace such that changes in the marketplace orchestration platform are automatically reflected in the digital twin. In embodiments, the workforce is a broker workforce for the marketplace. In embodiments, the workforce is a trading workforce for the marketplace. In embodiments, the workforce is a deal matching workforce for the marketplace. In embodiments, the workforce is a deal execution workforce for the marketplace. In embodiments, the role of at least one workforce is selected from among a trader role, a marketplace host role, a broker role, a buyer role, and a seller role. In embodiments, the role of at least one workforce is selected from among a market maker role, an exchange administrator role, a broker-dealer role, a trading role, a settlement role, a contract counterparty role, an exchange rate setting role, a marketplace orchestration role, a market setting role, and a contract setting role. In embodiments, the digital twin represents training recommendations for the workforce. In embodiments, the digital twin represents recommendations for augmenting the workforce. In embodiments, the digital twin provides recommendations for configuring a set of operations including the workforce.In embodiments, the digital twin provides recommendations for workforce composition.

[0021] Another aspect of the present invention relates to a marketplace orchestration platform that utilizes machine learning and artificial intelligence trained to recognize market stages. In embodiments, a machine learning system uses training data consisting of market characteristics and outcomes to train a set of machine learning models to output market stage-related decisions. In embodiments, an artificial intelligence system receives a request for a market stage-related decision and generates a market stage-related decision based on the set of machine learning models and the request. In embodiments, the market stage-related decision is utilized, at least in part, to automatically adjust market parameters. In embodiments, the set of machine learning models uses convolutional neural networks, recurrent neural networks, feedforward neural networks, long-term short-term memory (LTSM) neural networks, self-organizing neural networks, and hybrids and combinations thereof.

[0022] Another aspect of the present invention relates to a method for updating properties of market orchestration digital twins. The method can include receiving a request to update one or more properties of one or more digital twins. The method can include obtaining one or more digital twins necessary to fulfill the request. The method can include selecting a data source from a set of available data sources. The method can include obtaining data from the selected data source. The method can include updating one or more properties of the one or more digital twins based on the obtained data. In an embodiment, the digital twins are selected from the set of a marketplace digital twin, an asset digital twin, a trader digital twin, a broker digital twin, an environment digital twin, and a marketplace host digital twin. In an embodiment, one or more characteristics of the one or more digital twins are related to asset ownership. In an embodiment, the data source is selected from the set consisting of an Internet of Things connected device, a machine vision system, an analog vibration sensor, a digital vibration sensor, a fixed digital vibration sensor, a three-axis vibration sensor, a single-axis vibration sensor, an optical vibration sensor, and a crosspoint switch.

[0023] Another aspect of the present invention relates to a method for generating a fairness score for a set of transactions. The method may include receiving, by a fairness engine, transaction data from an execution engine. The method may include calculating, by the fairness engine, a fairness score representing the fairness of the transactions. In embodiments, the fairness engine may include an execution timing fairness engine that determines or receives a set of latency measures for a set of users. In embodiments, the execution timing fairness engine automatically configures a set of configuration parameters or other features that mitigate potential unfairness caused by varying latency. In embodiments, the set of latency measures is determined by testing network return times. In embodiments, testing network return times may include determining ping, upload speed, or download speed. In embodiments, the set of transactions is executed based on the fairness score exceeding a predetermined threshold.

[0024] Another aspect of the invention relates to a quantum computing system. In an embodiment, the quantum computing system is configured to determine exchange rates between, among, or across a set of markets by simulating a set of trading activity that includes the set of markets. In an embodiment, the quantum computing system supports a model selected from the set of quantum circuit models, quantum Turing models, adiabatic quantum computers, one-way quantum computers, quantum annealing, quantum cellular autonomas, and hybrids and combinations of the foregoing.

[0025] Another aspect of the present invention relates to a counterparty strategy engine. In an embodiment, the counterparty strategy engine includes a machine learning system that uses training data including market characteristics and outcomes to train a set of machine learning models to output decisions related to a trading strategy adopted by a set of counterparties. In an embodiment, the counterparty strategy engine includes an artificial intelligence system that receives a request for a decision related to a trading strategy adopted by a set of counterparties and generates a decision related to the strategy adopted by the set of counterparties based on the set of machine learning models and the request. In an embodiment, the trading strategy is selected from the set of buy-and-hold, equity long / short, asset allocation, intertemporal portfolio selection, pairs trading, swing trading, scalping, day trading, news-based, market timing, social trading, front-running, chart-based, computer science-based, automated / algorithmic, and hybrids and combinations of the foregoing.

[0026] Another aspect of the present disclosure relates to a machine learning and / or artificial intelligence system trained to group similar buyers into cohort-targeted marketplaces. In embodiments, the machine learning system uses training data including marketplace characteristics and outcomes to train a set of machine learning models to identify sets of similar buyers for cohort-targeted markets. In embodiments, the artificial intelligence system receives a request to identify groups of similar buyers, identifies the groups of similar buyers, and generates cohort-targeted marketplaces based on the identification. In embodiments, the set of machine learning models employ convolutional neural networks, recurrent neural networks, feedforward neural networks, long-term short-term memory (LTSM) neural networks, self-organizing neural networks, and hybrids and combinations of the foregoing. In embodiments, content from a set of product websites may be fed to the set of machine learning models, which are trained to identify new product or service offerings relevant to the cohort-targeted marketplace.

[0027] Another aspect of the present disclosure relates to a quantum computing system configured to interface with and direct the neural network development or selection process. In embodiments, the quantum computing system directly programs the neural network weights so that the neural network generates a desired output. In embodiments, the quantum computing system supports a model selected from the set of quantum circuit models, quantum Turing models, adiabatic quantum computers, one-way quantum computers, quantum annealing, quantum cellular autonomies, and hybrids and combinations of the foregoing.

[0028] Exemplary embodiments herein disclose systems, procedures, and aspects that provide a cryptographically secure blockchain for knowledge systems that can store digital knowledge to provide convenient and secure control of the same. Exemplary methods and systems herein provide improvements in determining real estate valuations, trust in an entity's financial health, transparency, information symmetry, and the application and negotiation process in lending environments. Exemplary methods and systems herein provide improvements to market-enabling machinery, providing increased efficiency, speed, and / or reliability for participants in such markets. Exemplary methods and systems herein provide improvements to data collection, storage, and processing, automated configuration of inputs, resources, and outputs, and facilities optimization for energy and computing facilities.

[0029] In one or more exemplary embodiments, a knowledge distribution system for controlling rights associated with digital knowledge is disclosed. The knowledge distribution system may be a blockchain system for knowledge that enables the storage, buying and selling of digital knowledge, tokenization of digital knowledge, and / or review / audit of digital knowledge via a cryptographically secure distributed ledger. Smart contracts can be implemented on the distributed ledger to control rights to digital knowledge, transfer digital knowledge, and ensure parties adhere to contracts related to digital knowledge. The blockchain for knowledge system can also facilitate third parties to review, audit, or verify information associated with digital knowledge.

[0030] Knowledge sharing can have many practical obstacles, such as a lack of trust between parties who may benefit from knowledge sharing. Digital knowledge distribution systems offer platforms that can facilitate the orchestration of knowledge sharing by providing a high degree of control over the extent to which trading partners have access to shared knowledge. Even when knowledge is secure and well-managed, some types of knowledge are sensitive enough that owners may not want to share the entire set with a single party. In embodiments, a platform for a digital knowledge distribution system is disclosed that facilitates the processing and control of knowledge subsets, including the aggregation of knowledge resulting from the partitioning of the knowledge subsets, or the automated processing of associated outputs.

[0031] The knowledge distribution system may include a ledger management system configured to create and manage a distributed ledger, which may be distributed across nodes of a network and may include cryptographically linked blocks. The smart contract system may communicate with the distributed ledger and be configured to implement and manage smart contracts via the distributed ledger. The smart contract may be stored in the distributed ledger and may include a trigger event. The smart contract may be configured to execute smart contract actions with respect to the digital knowledge in response to the occurrence of a trigger event. The knowledge distribution system may be configured to receive instances of digital knowledge from users. The digital knowledge may be tokenized such that the instances of digital knowledge may be manipulated as tokens on the distributed ledger. The tokenized digital knowledge may be stored via the distributed ledger. Commitments of the parties to the smart contract may be processed. The knowledge distribution system may be configured to manage control and access rights to the tokenized digital knowledge according to the smart contract and to manage smart contract actions in response to a trigger event.

[0032] One or more of the following exemplary features may be included: The digital knowledge may include intellectual property where a smart contract embeds intellectual property license terms for the embedded intellectual property in a distributed ledger, and where executing operations on the distributed ledger may provide access to the intellectual property and process commitments of the parties to the smart contract to the intellectual property license terms. A smart contract wrapper on a distributed ledger may enable operations on the ledger to add the intellectual property to an aggregate stack of intellectual property, enable operations on the ledger to agree on royalty allocations between parties in the ledger, enable operations on the ledger to add the intellectual property to an aggregate stack of intellectual property, and / or enable operations on the ledger to process commitments of the parties to the contract terms. The tokenized digital knowledge may include an instruction set. The distributed ledger may be configured to provide provable access to the instruction set and execute the instruction set on a system that results in recording a transaction on the distributed ledger. The tokenized digital knowledge may include executable algorithmic logic, a three-dimensional (3D) printer instruction set, a coating process instruction set, a semiconductor manufacturing process instruction set, a firmware program, a field programmable gate array instruction set, serverless code logic, a crystal manufacturing system instruction set, a food preparation process instruction set, a polymer manufacturing process instruction set, a chemical synthesis process instruction set, a biological manufacturing process instruction set, a digital twin dataset, and / or an expert-wrapped trade secret. The system may be configured to aggregate views of the trade secret into a chain of proof that each knowledge recipient of a party has viewed the trade secret. The knowledge distribution system may include a reporting system configured to report analytical results based on operations performed on the distributed ledger or the digital knowledge. The distributed ledger may be configured to aggregate instruction sets where an operation on the distributed ledger can add at least one instruction to an existing instruction set to provide a modified instruction set.The smart contract may be configured to manage the allocation of the instruction subset to the distributed ledger and access to the instruction subset. The distributed ledger may be configured to record parties that contributed to an instance of digital knowledge by storing data associated with the parties in at least one of the blocks. The knowledge distribution system may be configured to record the source of an instance of digital knowledge by storing data associated with the source in at least one of the blocks. The distributed ledger may be configured such that a private network of authorized participants establishes the cryptographically-based consensus necessary for validating new blocks to be added to the block. The ledger management system may be configured to facilitate crowdsourcing of information to be added to blocks of the distributed ledger. The distributed ledger may be configured to store crowdsourcer reviews of the instance of digital knowledge in blocks of blocks. The distributed ledger may be configured to store crowdsourcer signatures of the instance of digital knowledge in blocks of blocks. The distributed ledger may be configured to store crowdsourcer verifications of the instance of digital knowledge in blocks of blocks. The ledger management system may be configured to establish cryptocurrency tokens that can be traded between users of the distributed ledger. The knowledge distribution system may include an account management system in communication with the distributed ledger that may be configured to facilitate creation and management of user accounts associated with users of the knowledge distribution system. The knowledge distribution system may include a user interface system in communication with the distributed ledger that is configured to present a user interface to users of the knowledge distribution system, where the user interface may be capable of enabling users to view data associated with the instances of digital knowledge. The knowledge distribution system may include a marketplace system in communication with the distributed ledger that is configured to establish and maintain a digital marketplace that may be configured to visually present data associated with the instances of digital knowledge to users of the knowledge distribution system.The knowledge distribution system may include a knowledge data store in communication with the distributed ledger and configured to store data related to the digital knowledge. The knowledge distribution system may include a client data store in communication with the distributed ledger and configured to store data related to users of the knowledge distribution system. The knowledge distribution system may include a smart contract data store in communication with the distributed ledger and configured to store data related to smart contracts. The knowledge distribution system may include a reporting system in communication with the distributed ledger and configured to analyze the tokenized digital knowledge and report analysis results based on the analysis of the tokenized digital knowledge. The smart contract may be generated using a parameterizable smart contract template. The smart contract may include parameters based on the type of digital knowledge being tokenized. The parameters may include financial parameters, royalty parameters, usage parameters, generated output parameters, consideration allocation parameters, identity parameters, and / or access condition parameters.

[0033] In other exemplary embodiments, the knowledge distribution system may use distributed ledgers and smart contracts to facilitate the management and exchange of access, licensing, and ownership of digital knowledge.

[0034] In another exemplary embodiment, a computer-implemented method for controlling rights associated with digital knowledge is disclosed. The method may include creating and managing a distributed ledger distributed across nodes of a network and including cryptographically linked blocks. A smart contract may be implemented and managed via the distributed ledger, and the smart contract may be stored on the distributed ledger and may include a trigger event. In response to the occurrence of the trigger event, a smart contract action may be executed with respect to the digital knowledge. An instance of the digital knowledge may be received. The digital knowledge may be tokenized such that the instance of the digital knowledge may be manipulated as a token on the distributed ledger. The tokenized digital knowledge may be stored via the distributed ledger. Commitments of parties to the smart contract may be processed. The method may include managing rights to control and access the tokenized digital knowledge in accordance with the smart contract and managing smart contract actions in response to the trigger event.

[0035] One or more of the following example features may be included: A knowledge exchange for the exchange of tokenized digital knowledge based on smart contracts may be orchestrated. The knowledge exchange of tokenized digital knowledge may be integrated with other exchanges, where the knowledge exchange facilitates the exchange of valuable and / or sensitive knowledge related to the subject matter of the other exchanges.

[0036] In another exemplary embodiment, a knowledge distribution system for controlling rights associated with digital knowledge is disclosed. The knowledge distribution system may include a ledger management system configured to create and manage a distributed ledger. The distributed ledger may be distributed across nodes of a network and may include cryptographically linked blocks. A smart contract system may communicate with the distributed ledger and may be configured to implement and manage smart contracts via the distributed ledger. The smart contract may be stored in the distributed ledger and may include a trigger event. The smart contract may be configured to execute a smart contract action with respect to the digital knowledge in response to the occurrence of the trigger event. The knowledge distribution system may be configured to receive, from a knowledge provider device, an instance of digital knowledge including a three-dimensional (3D) printer instruction set for 3D printing an object. The digital knowledge may be tokenized such that the instance of digital knowledge can be manipulated as a token on the distributed ledger. The tokenized digital knowledge may be stored via the distributed ledger. Commitments of knowledge providers and knowledge recipients of the 3D printer instruction set to the smart contract may be processed. The knowledge distribution system may be configured to manage control and access rights of tokenized digital knowledge according to smart contracts, and may manage smart contract actions according to conditions and trigger events.

[0037] One or more of the following exemplary features may be included: The 3D printer instruction set may include a 3D printing schematic. The object may be at least one of a custom part, a custom product, a manufacturing part, a replacement part, a toy, a medical device, and a tool. The knowledge recipient may download and use the 3D printer instruction set using a knowledge recipient device. The knowledge recipient device may be at least one of a computing device, a server, a 3D printer, and a manufacturing device. The knowledge recipient may purchase tokenized digital knowledge corresponding to the 3D printer instruction set using the knowledge recipient device. The knowledge distribution system may include an event listener configured to listen to an application programming interface (API) that may provide a connection between the knowledge distribution system and the knowledge recipient's knowledge recipient device. The smart contract may be configured to trigger a condition that the knowledge recipient makes payment if the 3D printer instruction set may be transferred or used based on control and access rights of the tokenized digital knowledge. The control and access rights of the tokenized digital knowledge may include permission for a user to 3D print using multiple instances of the 3D printer instruction set. The control and access rights of the tokenized digital knowledge may include at least one of the following: 3D printer requirements, a time period during which the object may be 3D printed, whether the tokenized digital knowledge will be transferred to downstream knowledge recipients, and warranties, disclaimers, indemnifications, and certifications regarding the object. Information related to the 3D printer instruction set of the tokenized digital knowledge may be changed on the distributed ledger when the 3D printer instruction set is purchased, downloaded, or used. In an example, the information related to the 3D printer instruction set may include at least one of origin, creation date, names of one or more contributing individuals, groups, and / or companies, price, market trends for associated schematics, serial number, and part identifier.The smart contract actions may include assigning a serial number to the 3D printed object, monitoring for trigger events, verifying fulfillment of obligations based on conditions, verifying payment and / or transfer of tokenized digital knowledge, transferring the tokenized digital knowledge, recording one or more transactions on the distributed ledger, performing one or more operations on the distributed ledger, or generating one or more new blocks on the distributed ledger. The smart contract actions may include verifying that conditions are met as defined in the smart contract, where the conditions may be one of printer requirements, payment or currency received from the knowledge recipient's knowledge recipient device, and transfer of the tokenized digital knowledge to the knowledge recipient's knowledge recipient device. When the tokenized digital knowledge can be transferred to the knowledge recipient's knowledge recipient device, a 3D printer may be configured to print the object according to the 3D printer instruction set. The knowledge distribution system may include a smart contract generator that may be configured to parameterize a smart contract template based on at least one of information provided by the knowledge provider, conditions, and trigger events.

[0038] In another exemplary embodiment, a computer-implemented method for controlling rights associated with digital knowledge is disclosed. The method may include creating and managing a distributed ledger distributed across nodes of a network and including cryptographically linked blocks. A smart contract may be implemented and managed via the distributed ledger, and the smart contract may be stored on the distributed ledger and may include a trigger event. In response to the occurrence of the trigger event, a smart contract action may be executed with respect to the digital knowledge. The method may include receiving, from a knowledge-providing device, an instance of digital knowledge including a three-dimensional (3D) printer instruction set for 3D printing an object. The digital knowledge may be tokenized such that the instance of digital knowledge can be manipulated as a token on the distributed ledger. The tokenized digital knowledge may be stored via the distributed ledger. Commitments of knowledge providers and knowledge recipients of the 3D printer instruction set to the smart contract may be processed. The method may include managing control and access rights to the tokenized digital knowledge in accordance with the smart contract and managing smart contract actions in accordance with conditions and trigger events.

[0039] One or more of the following example features may be included: Elements of the instance of digital knowledge may be crowdsourced via smart contracts. Elements of the instance of digital knowledge may be managed by a smart contract system in accordance with smart contracts.

[0040] Provided herein is a lending transaction enablement platform having a set of data integration microservices, including data collection and monitoring services, blockchain services, and smart contract services, for processing lending entities and transactions. The platform can enable a wide range of specialized solutions, which can share data collection and storage infrastructure and may share or exchange inputs, events, activities, and outputs to enhance learning, enable automation, and enable adaptive intelligence across various solutions.

[0041] An aspect of the present disclosure relates to a method for electronically facilitating the licensing of one or more moral rights of a licensor. The method may include receiving an access request from a licensee to obtain approval to license the moral rights from a set of available licensors. The method may include selectively granting access to the licensee based on the access request. The method may include receiving confirmation of deposit of a fund amount from the licensee. The method may include issuing cryptocurrency to the licensee's account in an amount corresponding to the fund amount deposited by the licensee. The method may include receiving a smart contract request to create a smart contract governing the licensing of one or more moral rights of the licensor by the licensee. The smart contract request may indicate one or more terms, including a cryptocurrency consideration amount to be paid to the licensor in exchange for one or more obligations of the licensor. The method may include generating a smart contract based on the smart contract request. The method may include escrowing the cryptocurrency consideration amount from the licensee's account. The method may include deploying the smart contract to a distributed ledger. The method can include verifying that the licensor has fulfilled the one or more obligations according to the smart contract. The method can include releasing at least a portion of the cryptocurrency consideration to a licensor account of the licensor in response to receiving verification that the licensor has fulfilled the one or more obligations. The method can include outputting a record to the distributed ledger indicating completion of the license transaction defined by the smart contract.

[0042] Another aspect of the present disclosure relates to a system configured for electronically facilitating the licensing of one or more moral rights of a licensor. The system may include one or more hardware processors configured with machine-readable instructions. The processor(s) may be configured to receive an access request from a licensee to obtain approval to license the moral rights from a set of available licensors. The processor(s) may be configured to selectively grant access to the licensee based on the access request. The processor(s) may be configured to receive a confirmation of deposit of an amount from the licensee. The processor(s) may be configured to issue cryptocurrency to the licensee's account in an amount corresponding to the amount of funds deposited by the licensee. The processor(s) may be configured to receive a smart contract request for creating a smart contract governing the licensing of one or more moral rights of the licensor by the licensee. The smart contract request may indicate one or more conditions, including a cryptocurrency consideration amount to be paid to the licensor in exchange for one or more obligations of the licensor. The processor(s) may be configured to generate the smart contract based on the smart contract request. The processor(s) may be configured to escrow a cryptocurrency value from the licensee's account. The processor(s) may be configured to deploy the smart contract to a distributed ledger. The processor(s) may be configured to verify that the licensor has fulfilled one or more obligations according to the smart contract. The processor(s) may be configured to release at least a portion of the cryptocurrency value to the licensor's account in response to receiving verification that the licensor has fulfilled the one or more obligations. The processor(s) may be configured to output a record to the distributed ledger indicating completion of the license transaction defined by the smart contract.

[0043] These and other features, as well as the characteristics of the present technology, and the method of operation and function of associated elements of construction, and combination of parts and economies of manufacture, will become more apparent from a consideration of the following description and appended claims, with reference to the accompanying drawings, all of which form a part of this specification, and like reference numerals designate corresponding parts in the various views. It is to be expressly understood, however, that the drawings are for the purpose of illustration and description only and are not intended as a definition of the limits of the invention. As used in this specification and in the claims, the singular forms "a," "an," and "the" include plural references unless the context clearly dictates otherwise. A more complete understanding of the present disclosure will be understood from the following description and the accompanying drawings, and the claims.

[0044] (Brief description of the accompanying drawings) The present disclosure and the following detailed description of certain embodiments thereof can be understood by reference to the following figures. [Brief explanation of the drawings]

[0045] [Figure 1] FIG. 1 is a schematic diagram of components of a platform for enabling intelligent transactions according to an embodiment of the present disclosure.

[0046] [Figure 2A] 2A and 2B are schematic diagrams of additional components of a platform for enabling intelligent transactions according to embodiments of the present disclosure. [Figure 2B] 2A and 2B are schematic diagrams of additional components of a platform for enabling intelligent transactions according to embodiments of the present disclosure.

[0047] [Figure 3] FIG. 3 is a schematic diagram of additional components of a platform for enabling intelligent transactions according to an embodiment of the present disclosure.

[0048] [Figure 4] 4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 5] 4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 6] 4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 7] 4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 8]4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 9] 4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 10] 4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 11] 4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 12]4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 13] 4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 14] 4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 15] 4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 16]4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 17] 4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 18] 4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 19] 4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 20]4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 21] 4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 22] 4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 23] 4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 24]4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 25] 4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 26] 4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 27] 4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 28]4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 29] 4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 30] 4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure. [Figure 31] 4-31 are schematic diagrams of embodiments of neural net systems that enable intelligent transactions, including those involving expert systems, self-organization, machine learning, and artificial intelligence, and that may be connected, integrated, and accessed by a platform including neural net systems trained for pattern recognition, classification of one or more parameters, characteristics, or phenomena, support for autonomous control, and other purposes, in accordance with embodiments of the present disclosure.

[0049] [Figure 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, according to an embodiment of the present disclosure.

[0050] [Figure 33] Figure 33 shows the components and interactions of the trading, financial, and marketplace enabling system.

[0051] [Figure 34] FIG. 34 is a diagram illustrating the components and interactions of a series of data processing layers of the exchange financial market realization system.

[0052] [Figure 35] Figure 35 illustrates the adaptive intelligence and robotic process automation capabilities of trading, financial, and marketplace enabling systems.

[0053] [Figure 36] Figure 36 illustrates the opportunity mining capabilities of the trading, financial, and marketplace enabling system.

[0054] [Figure 37] Figure 37 illustrates the adaptive edge compute management and edge intelligence capabilities of the system to enable trading, finance, and markets.

[0055] [Figure 38] FIG. 38 illustrates the protocol adaptation and adaptive data storage capabilities of the transactional, financial, and marketplace enabling system.

[0056] [Figure 39]FIG. 39 illustrates the robotics operational analysis capabilities of the trading finance market enabling system.

[0057] [Figure 40] Figure 40 illustrates a blockchain and smart contract platform for a forward market for access rights to events.

[0058] [Figure 41] Figure 41 illustrates the algorithm and dashboard of a blockchain and smart contract platform for a forward market for access rights to events.

[0059] [Figure 42] Figure 42 illustrates a blockchain and smart contract platform for forward market demand aggregation.

[0060] [Figure 43] Figure 43 illustrates the algorithm and dashboard of a blockchain and smart contract platform for forward market demand aggregation.

[0061] [Figure 44] Figure 44 illustrates a blockchain and smart contract platform for crowdsourcing for innovation.

[0062] [Figure 45] Figure 45 illustrates the algorithm and dashboard of a blockchain and smart contract platform for crowdsourcing for innovation.

[0063] [Figure 46] Figure 46 illustrates a blockchain and smart contract platform for crowdsourcing evidence.

[0064] [Figure 47] FIG. 47 illustrates the algorithm and dashboard of a blockchain and smart contract platform for crowdsourcing for evidence.

[0065] [Figure 48] Figure 48 depicts 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.

[0066] [Figure 49] Figure 49 illustrates the components and interactions of an embodiment of a lending platform in which a suite of lending solutions is supported by a data integration set of data collection and monitoring services, adaptive intelligent systems, and data storage systems.

[0067] [Figure 50] Figure 50 illustrates the 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 about entities involved in or related to lending transactions.

[0068] [Figure 51] Figure 51 depicts the components and interactions of a lending platform having an Internet of Things and sensor platform for monitoring at least one of the set of assets, set of collateral, and guarantees for a loan, bond, or debt transaction.

[0069] [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 a lending transaction.

[0070] [Figure 53] FIG. 53 illustrates one embodiment of a crowdsourcing workflow implemented by a lending platform.

[0071] [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 analytics services, and a set of data collection and monitoring services.

[0072] [Figure 55] FIG. 55 illustrates the components and interactions of an embodiment of a lending platform with smart contracts that automatically restructure debt based on monitored conditions.

[0073] [Figure 56] Figure 56 illustrates the components and interactions of a lending platform with a series of data collection and monitoring systems for verifying the authenticity of guarantees for loans, including an Internet of Things system and a social network analysis system.

[0074] [Figure 57] FIG. 57 illustrates the components and interactions of a lending platform with a robotic process automation system for negotiating a set of terms for a loan.

[0075] [Figure 58]FIG. 58 illustrates the components and interactions of a lending platform with a robotic process automation system for loan collection.

[0076] [Figure 59] Figure 59 shows the components and interactions of a lending platform with a robotic process automation system for integrating a series of loans.

[0077] [Figure 60] FIG. 60 illustrates the components and interactions of a lending platform with a robotic process automation system for managing factored loans.

[0078] [Figure 61] Figure 61 shows the components and interactions of a lending platform with a robotic process automation system for brokering mortgage loans.

[0079] [Figure 62] FIG. 62 illustrates the components and interactions of a lending platform with a crowdsourcing and automated classification system for verifying issuer terms for bonds, a social network monitoring system with artificial intelligence for classifying terms on bonds, and an Internet of Things data collection and monitoring system with artificial intelligence for classifying terms on bonds.

[0080] [Figure 63] FIG. 63 illustrates the components and interactions of a lending platform having a system for managing loan terms based on parameters monitored by IoT, determined by a social network analysis system, or determined by a crowdsourcing system.

[0081] [Figure 64]FIG. 64 illustrates the components and interactions of a lending platform with automated blockchain custody services for managing a set of custodial assets.

[0082] [Figure 65] Figure 65 illustrates the components and interactions of a lending platform with 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 lending entities and transactions.

[0083] [Figure 66] Figure 66 illustrates the components and interactions of a lending platform having a loan marketing system with a set of data integration microservices including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for marketing loans to a set of prospective customers.

[0084] [Figure 67] Figure 67 illustrates the components and interactions of a lending platform having a rating system with a set of data integration microservices, including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services, for rating a set of loan-related entities.

[0085] [Figure 68] Figure 68 illustrates the 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.

[0086] [Figure 69] FIG. 69 is a diagram illustrating a system for automating loan management.

[0087] [Figure 70] FIG. 70 shows an example of the system.

[0088] [Figure 71] FIG. 71 is a diagram illustrating how a loan is processed.

[0089] [Figure 72] Figure 72 shows a system for adaptive intelligence and bottic process automation capabilities that enable trading, finance, and marketplaces.

[0090] [Figure 73] Figure 73 illustrates how smart contract creation and collateral allocation can be automated.

[0091] [Figure 74] FIG. 74 is a diagram illustrating a system for handling loans.

[0092] [Figure 75] FIG. 75 is a diagram illustrating how a loan is processed.

[0093] [Figure 76] FIG. 76 is a diagram illustrating a system for adaptive intelligence and robotic process automation.

[0094] [Figure 77] FIG. 77 is a diagram illustrating a loan creation and management method.

[0095] [Figure 78]Figure 78 shows a system for adaptive intelligence and robotic process automation capabilities that enable transactions, finance, and marketplaces.

[0096] [Figure 79] Figure 79 illustrates a method for robotic process automation of trading, financial and market activities.

[0097] [Figure 80] FIG. 80 is a diagram illustrating a system for adaptive intelligence and robotic process automation.

[0098] [Figure 81] Figure 81 shows how trading, financial and market activities can be automated.

[0099] [Figure 82] FIG. 82 is a diagram illustrating a system for adaptive intelligent robotic processing.

[0100] [Figure 83] FIG. 83 illustrates a method for performing loan-related actions.

[0101] [Figure 84] FIG. 84 is a diagram illustrating a system for adaptive intelligent robotic processing.

[0102] [Figure 85] FIG. 85 illustrates a method for performing loan-related actions.

[0103] [Figure 86] FIG. 86 is a diagram illustrating a system for adaptive intelligent robotic processing.

[0104] [Figure 87] FIG. 87 illustrates a method for performing loan-related actions.

[0105] [Figure 88] Figure 88 illustrates a smart contract system for managing loan collateral.

[0106] [Figure 89] Figure 89 illustrates a smart contract method for managing collateral for a loan.

[0107] [Figure 90] Figure 90 shows a system for verifying collateral and guarantor conditions for a loan.

[0108] [Figure 91] Figure 91 shows a crowdsourcing method for verifying collateral and guarantor requirements for loans.

[0109] [Figure 92] Figure 92 illustrates a smart contract system for modifying a loan.

[0110] [Figure 93] Figure 93 illustrates a smart contract method for modifying a loan.

[0111] [Figure 94] Figure 94 illustrates a smart contract system for modifying a loan.

[0112] [Figure 95] Figure 95 illustrates a smart contract method for modifying a loan.

[0113] [Figure 96] Figure 96 illustrates a smart contract system for modifying a loan.

[0114] [Figure 97]Figure 97 illustrates a smart contract method for modifying a loan.

[0115] [Figure 98] FIG. 98 illustrates a monitoring system for verifying the terms of a guarantee for a loan.

[0116] [Figure 99] FIG. 99 illustrates a monitoring method for verifying the terms of a guarantee for a loan.

[0117] [Figure 100] FIG. 100 illustrates a robotic process automation system for loan negotiation.

[0118] [Figure 101] FIG. 101 illustrates a robotic process automation method for loan negotiation.

[0119] [Figure 102] FIG. 102 is a diagram illustrating a system for adaptive intelligence and robotic process automation.

[0120] [Figure 103] FIG. 103 is a diagram showing a lending and collection method.

[0121] [Figure 104] FIG. 104 is a diagram illustrating a system for adaptive intelligence and robotic process automation.

[0122] [Figure 105] FIG. 105 is a diagram showing how to refinance a loan.

[0123] [Figure 106] FIG. 106 is a diagram illustrating a system for adaptive intelligence and robotic process automation.

[0124] [Figure 107] Figure 107 is a diagram for the loan consolidation method.

[0125] [Figure 108] FIG. 108 is a diagram illustrating a system for adaptive intelligence and robotic process automation.

[0126] [Figure 109] Figure 109 is a diagram showing the loan factoring method.

[0127] [Figure 110] FIG. 110 is a diagram illustrating a system for adaptive intelligence and robotic process automation.

[0128] [Figure 111] FIG. 111 is a diagram showing a mortgage brokerage method.

[0129] [Figure 112] FIG. 112 is a diagram illustrating a system for adaptive intelligence and robotic process automation.

[0130] [Figure 113] Figure 113 shows the debt management method.

[0131] [Figure 114] FIG. 114 is a diagram illustrating a system for adaptive intelligence and robotic process automation.

[0132] [Figure 115] FIG. 115 is a diagram showing a method for managing bonds.

[0133] [Figure 116] FIG. 116 is a diagram showing a system for monitoring the status of bond issuers.

[0134] [Figure 117] FIG. 117 illustrates a method for monitoring the status of a bond issuer.

[0135] [Figure 118] FIG. 118 illustrates a system for monitoring the status of bond issuers.

[0136] [Figure 119] FIG. 119 illustrates a method for monitoring the status of a bond issuer.

[0137] [Figure 120] FIG. 120 is a diagram showing an automatic subsidy loan management system.

[0138] [Figure 121] FIG. 121 is a diagram showing a method for automatically changing the sub-loan conditions.

[0139] [Figure 122] FIG. 122 is a diagram showing a system for automatically changing loan terms.

[0140] [Figure 123] FIG. 123 illustrates a method for collecting social network information about entities involved in a subsidized loan transaction.

[0141] [Figure 124] FIG. 124 is a diagram illustrating a system for automating the handling of grants using crowdsourcing.

[0142] [Figure 125] FIG. 125 illustrates a method for automating the handling of subsidized loans.

[0143] [Figure 126] FIG. 126 is a diagram illustrating a system for asset access control.

[0144] [Figure 127] FIG. 127 is a diagram showing a method for controlling access to assets.

[0145] [Figure 128] Figure 128 shows how the system automatically processes loan foreclosures.

[0146] [Figure 129] FIG. 129 illustrates a method for facilitating the foreclosure of collateral.

[0147] [Figure 130] FIG. 130 is a diagram illustrating an example of an energy and computing resource platform.

[0148] [Figure 131] FIG. 131 is a diagram showing an example of an equipment data record.

[0149] [Figure 132] FIG. 132 is a diagram showing an example of a schema of a person data record.

[0150] [Figure 133] FIG. 133 is a diagram illustrating a cognitive processing system.

[0151] [Figure 134] FIG. 134 illustrates the process by which the lead generation system generates a lead list.

[0152] [Figure 135] FIG. 135 illustrates the process by which a lead generation system determines facility output for identified leads.

[0153] [Figure 136] FIG. 136 is a diagram showing a process for generating and outputting personalized content.

[0154] [Figure 137] FIG. 137 is a schematic diagram illustrating an example of a portion of an information technology system for transactional artificial intelligence utilizing digital twins, according to some embodiments of the present disclosure.

[0155] [Figure 138] FIG. 138 is a schematic diagram illustrating a compliance system that facilitates licensing of moral rights according to some embodiments of the present disclosure.

[0156] [Figure 139] FIG. 139 is a schematic diagram illustrating an example set of components of a compliance system according to some embodiments of the present disclosure.

[0157] [Figure 140] FIG. 140 illustrates a sequence of operations for a method of screening potential licensees for purposes of licensing moral rights of a licensor, according to some embodiments of the present disclosure.

[0158] [Figure 141] FIG. 141 illustrates a sequence of operations of a method for facilitating licensing of a licensor's moral rights by a licensee, according to some embodiments of the present disclosure.

[0159] [Figure 142] FIG. 142 illustrates a sequence of operations of a method for detecting potential circumvention of rules or regulations by a licensor and / or licensee, according to some embodiments of the present disclosure.

[0160] [Figure 143] Figure 143 is a diagram showing how to select an AI solution.

[0161] [Figure 144] Figure 144 is a diagram showing how to select an AI solution.

[0162] [Figure 145] Figure 145 shows an example of an assembled AI solution.

[0163] [Figure 146] Figure 146 is a diagram showing how to select an AI solution.

[0164] [Figure 147] Figure 147 is a diagram showing how to select an AI solution.

[0165] [Figure 148] Figure 148 is a diagram showing an AI solution selection and setting system.

[0166] [Figure 149] Figure 149 is a diagram showing an AI solution selection and setting system.

[0167] [Figure 150] Figure 150 is a diagram showing an AI solution selection and setting system.

[0168] [Figure 151] FIG. 151 is a diagram showing a component configuration circuit.

[0169] [Figure 152] Figure 152 is a diagram showing an AI solution selection and setting system.

[0170] [Figure 153] FIG. 153 illustrates a system for selecting and configuring an artificial intelligence model.

[0171] [Fig. 154] FIG. 154 is a diagram showing how to select and set an artificial intelligence model.

[0172] [Figure 155]FIG. 155 is a schematic diagram illustrating an example of the architecture of a digital twin system according to an embodiment of the present disclosure.

[0173] [Figure 156] FIG. 156 is a schematic diagram illustrating exemplary components of a digital twin management system according to an embodiment of the present disclosure.

[0174] [Figure 157] FIG. 157 is a schematic diagram illustrating an example of a digital twin I / O system interfacing with an environment, a digital twin system, and / or components thereof to provide bidirectional transfer of data between coupled components, according to an embodiment of the present disclosure.

[0175] [Figure 158] FIG. 158 is a schematic diagram illustrating an example of an identification state associated with an industrial environment that a digital twin system may identify and / or store for access by an intelligent system (e.g., a cognitive intelligence system) or user of the digital twin system, according to an embodiment of the present disclosure.

[0176] [Figure 159] FIG. 159 is a schematic diagram illustrating an exemplary embodiment of a method for updating a set of properties of a digital twin of the present disclosure on behalf of a client application and / or one or more embedded digital twins.

[0177] [Figure 160] FIG. 160 illustrates an exemplary embodiment of a display interface of the present disclosure rendering a digital twin of a dryer centrifuge with information related to the dryer centrifuge.

[0178] [Figure 161]FIG. 161 is a schematic diagram illustrating an exemplary embodiment of a method for updating a set of vibration fault level conditions of machine parts, such as bearings, in a digital twin of an industrial machine on behalf of a client application.

[0179] [Figure 162] FIG. 162 is a schematic diagram illustrating an exemplary embodiment of a method for updating a set of vibration severity unit values ​​for a machine part, such as a bearing, in a digital twin of a machine on behalf of a client application.

[0180] [Figure 163] FIG. 163 is a schematic diagram illustrating an exemplary embodiment of a method for updating a set of failure probability values ​​in a digital twin of a machine part on behalf of a client application.

[0181] [Fig. 164] FIG. 164 is a schematic diagram illustrating an exemplary embodiment of a method for updating a set of machine downtime probability values ​​in a digital twin of a manufacturing facility on behalf of a client application.

[0182] [Figure 165] FIG. 165 is a schematic diagram illustrating an exemplary embodiment of a method for updating a set of outage probability values ​​for manufacturing equipment in an enterprise digital twin on behalf of a client application.

[0183] [Figure 166] FIG. 166 is a schematic diagram illustrating an exemplary embodiment of a method for updating a cost set of machine downtime values ​​in a digital twin of a manufacturing facility.

[0184] [Figure 167] FIG. 167 is a schematic diagram illustrating an exemplary embodiment of a method for updating one or more manufacturing KPI values ​​in a digital twin of a manufacturing facility on behalf of a client application.

[0185] [Figure 168] FIG. 168 is a schematic diagram of components of a knowledge distribution system and communication network for facilitating the management of digital knowledge according to an embodiment of the present disclosure.

[0186] [Figure 169] FIG. 169 is a schematic diagram showing a ledger network of a knowledge distribution system according to an embodiment of the present disclosure.

[0187] [Figure 170] Figure 170 is a schematic diagram of the knowledge distribution system of Figure 168, including details of the smart contract and smart contract system of the knowledge distribution system according to an embodiment of the present disclosure.

[0188] [Figure 171] FIG. 171 is a schematic diagram illustrating multiple data stores in a knowledge distribution system according to an embodiment of the present disclosure.

[0189] [Fig. 172] FIG. 172 illustrates a method for deploying knowledge tokens and associated smart contracts through a knowledge distribution system according to an embodiment of the present disclosure.

[0190] [Figure 173] FIG. 173 illustrates a method for executing a high-level process flow of a smart contract for distributing digital knowledge through a knowledge distribution system, according to an embodiment of the present disclosure.

[0191] [Fig. 174] FIG. 174 is a schematic diagram of another embodiment of components of a knowledge distribution system and communication network for facilitating management of digital knowledge according to an embodiment of the present disclosure.

[0192] [Figure 175]FIG. 175 is a diagram showing a knowledge distribution system for managing rights related to digital knowledge.

[0193] [Figure 176] FIG. 176 illustrates a computer-implemented method for controlling rights in digital knowledge.

[0194] [Figure 177] FIG. 177 illustrates a computer-implemented method for controlling rights in digital knowledge.

[0195] [Figure 178] FIG. 178 shows a knowledge distribution system for controlling rights related to digital knowledge.

[0196] [Figure 179] Figure 179 shows possible components of a 3D printer instruction set.

[0197] [Figure 180] Figure 180 shows the possible contents of the tokenized digital knowledge.

[0198] [Figure 181] Figure 181 shows the possible actions of a smart contract.

[0199] [Figure 182] Figure 182 shows possible conditions for triggering events.

[0200] [Figure 183] Figure 183 shows the possible controls and access rights.

[0201] [Figure 184] Figure 184 shows possible trigger events.

[0202] [Figure 185] FIG. 185 illustrates a computer-implemented method for controlling rights in digital knowledge.

[0203] [Figure 186] FIG. 186 illustrates a computer-implemented method for controlling rights in digital knowledge.

[0204] [Figure 187] Figure 187 shows the potential of crowdsourcing.

[0205] [Figure 188] Figure 188 shows the possible contents of a distributed ledger.

[0206] [Figure 189] Figure 189 shows the possible parameters.

[0207] [Figure 190] FIG. 190 is a diagram showing an embodiment of a knowledge distribution system for controlling rights related to digital knowledge.

[0208] [Figure 191] 191-196 show embodiments of operations for controlling rights related to digital knowledge. [Figure 192] 191-196 show embodiments of operations for controlling rights related to digital knowledge. [Figure 193] 191-196 show embodiments of operations for controlling rights related to digital knowledge. [Figure 194] 191-196 show embodiments of operations for controlling rights related to digital knowledge. [Figure 195] 191-196 show embodiments of operations for controlling rights related to digital knowledge. [Figure 196]191-196 show embodiments of operations for controlling rights related to digital knowledge.

[0209] [Figure 197] FIG. 197 is a perspective view illustrating an example embodiment of a knowledge distribution system including a trust network for identifying potential fraudulent transactions using consensus trust scores and preventing such fraudulent transactions, according to some embodiments of the present disclosure.

[0210] [Figure 198] FIG. 198 illustrates an example method for describing the operation of the example trusted network illustrated in FIG. 197, according to some embodiments of the present disclosure.

[0211] [Figure 199] FIG. 199 is a perspective view illustrating a transaction being processed by a ledger network including multiple node computing devices, according to some embodiments of the present disclosure.

[0212] [Figure 200] Figure 200 is a schematic diagram illustrating an example of a knowledge distribution system including a digital marketplace configured to provide an environment that enables knowledge providers and knowledge recipients to engage in commercial transactions related to the transfer of digital knowledge, according to some embodiments of the present disclosure.

[0213] [Figure 201] FIG. 201 is a perspective view illustrating an example user interface of a digital marketplace configured to enable transactions and commerce between various users of a knowledge distribution system according to some embodiments of the present disclosure.

[0214] [Figure 202] FIG. 202 is a schematic diagram of an example embodiment of a marketplace orchestration system according to some embodiments of the present disclosure.

[0215] [Figure 203] FIG. 203 is a schematic diagram of an example embodiment of a market orchestration system including a marketplace configuration system for configuring and launching a marketplace.

[0216] [Figure 204] FIG. 204 is a schematic diagram illustrating an example embodiment of a method for configuring and launching a marketplace, according to some embodiments of the present disclosure.

[0217] [Figure 205] FIG. 205 is a diagram of an example embodiment of a market orchestration system including a robotic process automation system configured to automate internal marketplace workflows based on robotic process automation.

[0218] [Figure 206] FIG. 206 is a schematic diagram of an example embodiment of a marketplace orchestration system including edge devices configured to perform edge computation and intelligence.

[0219] [Figure 207] FIG. 207 is a schematic diagram of an example embodiment of a marketplace orchestration system including a digital twin system configured to integrate a set of adaptive edge computing systems with a marketplace orchestration digital twin.

[0220] [Figure 208] Figure 208 is a schematic diagram showing the configuration of a digital twin system. DETAILED DESCRIPTION OF THE INVENTION

[0221] The term "service / microservice" (and similar terms) used herein should be understood broadly. Without limiting 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, such as data collection circuitry, blockchain circuitry, artificial intelligence circuitry, and / or smart contract circuitry for processing lending entities and transactions. A service / microservice facilitates data handling and may include facilities for data extraction, transformation, and loading, data cleansing and deduplication facility, data normalization facility, data synchronization facility, data security facility, computation facility (e.g., facility for performing predefined computational operations on data streams and providing output streams), compression and decompression facility, analysis facility (e.g., providing automated production of data visualizations), data processing facility, and / or data storage facility (including storage retention, formatting, compression, migration, etc.), and others.

[0222] A service / microservice may include controllers, processors, network infrastructure, input / output devices, servers, client devices (e.g., laptops, desktops, 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., automatic 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 subscription 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, etc. A service may be distributed across multiple devices, and / or the functions of a service may be performed by one or more devices that cooperate to perform the given functions of the service.

[0223] A service / microservice may include an application programming interface that facilitates connectivity between components of a system (e.g., microservices) that execute the service and entities external to the system (e.g., programs, websites, user devices, etc.). Without limiting other aspects of the present disclosure, an example microservice that may be present in a particular embodiment is: (A) a microservice (application programming circuit) that: (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 events related to the loan, 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 governing at least one of the loan terms, loan-related events, and loan-related activities. Any of the services / microservices may be controlled by or be able to control the controller. Certain systems may not be considered services / microservices. For example, a point-of-sale device that simply charges a set fee for goods or services may not be a service. In another example, a service that tracks the cost of goods or services and triggers notifications when the value changes may not be the rating service itself, but may depend on the rating service and / or form part of the rating service in certain embodiments.It is understood 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 as described herein, but may not be a service or part of a service for other embodiments (e.g., when the functionality or capabilities of the circuit, controller, or device are not related to a service or microservice as described herein). In another example, a mobile device being operated by a user may form part of a service described herein at a first point in time (e.g., when the user accesses the functionality of the service via an application or other communication from the mobile device and / or when a monitoring function is performed via the mobile device) but may not form part of the service at a second point in 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). Accordingly, the benefits of the present disclosure may be applied in a wide variety of processes or systems, and any such process or system may be considered a service (or part of a service) herein.

[0224] One of ordinary skill in the art, having the benefit of the disclosure herein and knowledge of contemplated systems typically available to him or her, will be able to determine which aspects of the present disclosure will benefit a particular system and how to combine processes and systems from the present disclosure to construct and provide performance characteristics (e.g., bandwidth, computational power, time response, etc.) and / or operational capabilities (e.g., time between checks, uptime requirements including longitudinal (e.g., continuous operating 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), sufficient service components to provide a given embodiment of the services, platforms, and / or microservices described herein. Specific considerations of one skilled in the art when determining the configuration of components, circuits, controllers, and / or devices for implementing a service, platform, and / or microservice ("Service" in the list below) as described herein include, but are not limited to, the balance of capital costs versus operational costs of implementing and operating the service; the availability, speed, and / or bandwidth of network services available to system components, service users, and / or other entities interacting with the service; response time considerations for the service (e.g., how quickly decisions within the service must be executed to support the commercial functionality of the service; the operation time of various artificial intelligence or other computationally intensive operations); the location of interacting components of the service and the impact of that location on the operation of the service (e.g., regulatory schemes related to data storage location, network communication limitations and / or costs, power costs as a function of location, availability of support for time periods relevant to the service, etc.); the availability of particular sensor types, associated support for those sensors, and the availability of sufficient substitutes (e.g., cameras may require supporting lighting).(Cameras may require supporting lighting and / or high network bandwidth or local storage for sensing purposes), aspects of the value underlying an aspect of the service, including the time sensitivity of the underlying value (e.g., if it changes rapidly or slowly in relation to the operation of the service or the term of the loan), including the principal amount of the loan (e.g., the value of the collateral, the volatility of the collateral value, the net worth or relative net worth of the lender, guarantor, and / or borrower, etc.), trust metrics between the parties to the transaction (e.g., performance history between the parties, credit ratings, social ratings, or other external metrics, conformance of the activities related to the transaction to industry standards or other normalized transaction types, etc.), and / or the availability of cost recovery options (e.g., subscriptions, fees, payments for services, etc.) for a given configuration and / or functionality of the service, platform, and / or microservices. Without limiting other aspects of the disclosure, specific operations performed by the services herein include making real-time changes to loans based on tracked data, utilizing the data to execute secured smart contracts, revaluing debt transactions in response to tracked terms or data, etc. While specific examples of services / microservices and considerations are described herein for illustrative purposes, any system that would benefit 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 this disclosure.

[0225] Services include, but are not limited to, financial services (e.g., loan transaction services), data collection services (e.g., data collection services that collect and monitor data), blockchain services (e.g., blockchain services that securely maintain data), data integration services (e.g., data integration services that aggregate data), smart contract services (e.g., smart contract services that determine aspects of smart contracts), software services (e.g., software services that extract data related to entities from publicly available information sites), crowdsourcing services (e.g., crowdsourcing services that solicit and report information), Internet of Things services (e.g., Internet of Things services that monitor the environment), publishing services (e.g., public services that publish data), and the like. development service), 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., for grouping collateral items based on attribute similarities), social network services (e.g., allowing configuration of social network parameters), asset identification services (e.g., for identifying sets of assets that a financial institution is responsible for custody of), identity management services (e.g., for verifying identities and credentials by a financial institution), etc., and / or similar functional terms may be used.Exemplary services performing one or more functions herein include computing devices, servers, networked devices, user interfaces, communication protocols, shared information and / or information storage, and / or device-to-device interfaces such as application programming interfaces (APIs), sensors (e.g., IoT sensors operatively coupled to monitored components, equipment, locations, etc.), distributed ledgers, circuitry, and computer-readable code configured to cause a processor to perform one or more functions of the service. One or more aspects or components of a service herein may be distributed across multiple devices and / or integrated in whole or in part into a given device. In embodiments, aspects or components of a service herein may be implemented at least in part through circuitry such as, by way of non-limiting example, 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 aggregation service implemented at least in part as a data aggregation circuit structured to aggregate data, or a smart contract service implemented at least in part as a smart contract circuit structured to determine aspects of a smart contract. a software service implemented at least in part as a software service circuit configured to extract data relating to an entity from a public information site; a crowdsourcing service implemented at least in part as a crowdsourcing circuit configured to solicit and report information; an IoT service implemented at least in part as an IoT circuit configured to monitor an environment; a publishing service implemented at least in part as a publishing service circuit configured to publish data; and a microservice service implemented at least in part as a microservice circuit configured for interconnection of a plurality of service circuits.a valuation service implemented at least partially as a valuation service circuit configured to access a valuation model to set a value for collateral based on data; an artificial intelligence service implemented at least partially as an artificial intelligence service circuit; a market value data collection service implemented at least partially as a market value data collection service circuit configured to monitor and report market information; a clustering service implemented at least partially as a clustering service circuit configured to group collateral items based on attribute similarities; a social networking service implemented at least partially as a social network analysis service circuit configured to set parameters for a social network; an asset identification service implemented at least partially 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 partially as an identity management service circuit that enables a financial institution to verify identities and entitlements; etc. Thus, the benefits of the present disclosure may be applied in a wide variety of systems, and any such system may be considered with respect to the items and services herein, although in certain embodiments, a given system may not be considered with respect to the items and services herein. A person skilled in the art with the benefit of the disclosure herein and knowledge of 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 processes and systems from the present disclosure can be combined to enhance the operation of a contemplated system. Among the considerations one skilled in the art may contemplate in determining a 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 desired aspects of security and verification of information communication for 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.Cost considerations for the Services, including capital and operating expenses, and which party or entity will bear the costs and the availability of recovering costs through subscriptions, service fees, or the like; the amount of information stored and / or communicated in support of the Services; and / or the processing or computing power utilized in support of the Services.

[0226] The terms "items and services" (and similar terms) used herein should be understood broadly. Without limiting other aspects or descriptions of this disclosure, items and services include, but are not limited to, any items and services used as compensation, used as collateral, the subject of negotiation, etc. Applications seeking guarantees or security for items that are the subject of a loan, collateral for a loan, or the like, such as products, services, offerings, solutions, physical products, software, service levels, service quality, financial instruments, debt, collateral, performance of services, or other items. Without limiting other aspects or descriptions of the present disclosure, the items and services may apply 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 property), financial items (e.g., commodities, securities, currency, securities, tickets, cryptocurrencies), consumables (e.g., food products, beverages), high-value items (e.g., precious metals, jewelry, gemstones), intellectual property (e.g., intellectual property items, intellectual property rights, contract rights), etc. Thus, the benefits of the present disclosure may be applied in a wide variety of systems, and any such system may be considered with respect to the items and services herein, although in certain embodiments, a given system may not be considered with respect to the items and services herein. One skilled 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 processes and systems from the present disclosure can be combined to enhance the operation of a contemplated system.

[0227] The terms agent, automated agent, and similar terms used herein should be understood broadly. Without limiting other aspects or descriptions of the present disclosure, an agent or automated agent may process events related to at least one of the value, status, and ownership of an item of collateral or asset. The agent or automated agent may perform actions related to a loan, debt transaction, bond transaction, subsidized loan, etc., to which the collateral or asset is subject, such as in response to the processed events. The agent or automated agent may interact with the market for purposes such as collecting data, testing spot market transactions, executing trades, etc., and dynamic system behavior involves complex interactions that a user may wish to understand, predict, control, and / or optimize. Certain systems may not be considered agents or automated agents. 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 not in response to a processed event, it may not be performed by an agent or automated agent. Those skilled in the art with the benefit of the disclosure herein and knowledge of the contemplated systems typically available to them can readily determine which aspects of the present disclosure involve and / or benefit from agents or automated agents. Particular considerations for those skilled in the art, or embodiments of the present disclosure relating to agents or automated agents, include, but are not limited to, rules that determine when there has been a change in the value, condition, or ownership of an asset or collateral, and / or rules that determine whether a change warrants further action regarding a loan or other transaction, as well as other considerations. While particular examples of market values ​​and market information are described herein for illustrative purposes, any embodiment that benefits from the disclosure herein, and any considerations that would be understood by one skilled in the art with the benefit of the disclosure herein, are specifically contemplated within the scope of the present disclosure.

[0228] As used herein, market information, market value, and similar terms should be understood broadly. Without limiting other aspects or descriptions of the present 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 expected value placed on an item in a market or auction setting, or to pricing or financial data for items similar to the item, asset, or collateral in at least one public market. For a company, market value is its number of outstanding shares multiplied by its 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 collateral, issuers, sets of bonds, sets of assets, sets of subsidized loans, parties, etc. Market value can be dynamic in nature, as it depends on a variety of factors, from physical operating conditions to economic conditions and supply and demand dynamics. Market value may be affected by, and market intelligence may be driven by, proximity to other assets, the asset's inventory or supply, demand for the asset, the item's origin, the item's history, the underlying current value of the item's components, the entity's bankruptcy status, the entity's seizure status, the entity's contractual default status, 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 export control 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 entity's credentials, a set of entity's referrals, a set of entity's testimonials, a set of entity's behavior, the entity's location, and the entity's geolocation. In certain embodiments, the market value may include information such as the volatility of the value, the sensitivity of the value (e.g., relative to other parameters that have uncertainties associated with them), and / or the particular value of the evaluated object to a particular party (e.g., the object may be more valuable in the possession of a first party than in the possession of a second party).

[0229] Certain information may not be market information or market value. For example, if the variables related to value are not market-derived, they may be use value or investment value. In certain embodiments, investment value may be considered market value (e.g., if the evaluating party intends to use the asset as an investment if acquired), while in other embodiments, it may not be considered market value (e.g., if the evaluating party intends to immediately liquidate the investment if acquired). One of ordinary skill in the art with the benefit of the disclosure herein and knowledge of the contemplated systems typically available to such person can readily determine which aspects of the present disclosure benefit from market information or market value. For those skilled in the art, particular considerations in determining whether the term market value refers to an asset, item, collateral, good, or service are the presence of other similar assets in the market, changes in value by location, opening bids for items above list price, and other considerations. Specific examples of market value and market information are described herein for illustrative purposes; however, 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.

[0230] The terms allocate or assigned and similar terms used herein should be understood broadly. Without limiting other aspects or descriptions of the present disclosure, allocate describes the pro rata distribution or allocation of value, or the process of dividing and allocating value according to the rules of pro rata distribution. The allocation of value may involve multiple parties (e.g., multiple parties each being the beneficiary of a portion of the value), multiple transactions (e.g., transactions each utilizing a portion of the value), and / or many-to-many relationships (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, allocated value may refer to the distribution or allocation of economic benefits, real estate, collateral, etc. In certain embodiments, allocation may include value considerations to the parties. For example, a $10 million asset allocated 50 / 50 between two parties may result in one party taking credit for the allocation and the value resulting from the allocation being different if the parties have different value considerations for the asset. For example, a first type of transaction (eg, a long-term loan) may have a different valuation for a given asset than a second type of transaction (eg, a short-term line of credit).

[0231] Certain conditions and processes may not be relevant to allocated value. For example, the total value of an item may provide its inherent value, but not how much of that value is held by each identified entity. One of ordinary skill in the art with the benefit of this disclosure and knowledge of allocated value can readily determine which aspects of this disclosure will benefit a particular application for allocated value. Particular considerations for allocated value to one of ordinary skill in the art, or embodiments of the present disclosure, include, but are not limited to, the currency of the principal amount, the expected transaction type (loan, bond, or debt), the specific type of collateral, the loan-to-value ratio, the collateral-to-loan ratio, the total transaction / loan amount, the principal amount, the number of entities owed, the collateral value, and the like. While specific examples of allocated values ​​are described herein for illustrative purposes, any embodiment benefiting from this disclosure, and any considerations understood by one of ordinary skill in the art with the benefit of this disclosure, are specifically contemplated within the scope of this disclosure.

[0232] The term "financial condition" and similar terms used herein should be understood broadly. Without being limited to other aspects or descriptions of this disclosure, financial condition describes the current state of a company's assets, liabilities, and capital position at a given point in time or period. Financial condition may be recorded in financial statements. Financial condition may also include an assessment of a company's ability to withstand future risk scenarios and meet future or upcoming obligations. Financial condition may be based on a set of company attributes selected from the following: a published company valuation, a set of company-owned assets as shown by public records, a valuation of a set of company-owned assets, a company's bankruptcy status, a company's foreclosure status, a company's contract default status, a company's regulatory violation status, a company's criminal status, and a company's export control status. Examples of such attributes include a company's export control status, a company's embargo status, a company's tariff status, a company's tax status, a company's credit report, a company's credit rating, a company's website rating, a set of customer reviews for the company's products, a company's social network rating, a set of company credentials, a set of company referrals, a set of company testimonials, a set of company actions, a company's location, and a company's geolocation. Financial terms may also describe requirements or thresholds for a contract or loan. 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 is specifically conditioned on financial factors. Some conditions may not be financial. For example, a credit card balance alone may provide a clue to financial status, but may not by itself be sufficient to provide financial status. In another example, a payment schedule may determine how long a liability may remain on a company's balance sheet, but in a silo may not accurately provide financial status. One skilled in the art with the benefit of this disclosure and knowledge of the contemplated systems typically available to such person can readily determine which aspects of the present disclosure involve and / or benefit from financial status.To those skilled in the art, particular considerations in determining whether the term financial condition refers to the current state of an entity's assets, liabilities, and capital position at a defined point in time or period, and / or for a given purpose, include reporting of one or more financial data points, loan to collateral value ratios, loan to collateral ratios, total transaction / loan amounts, borrower and lender credit scores, and other considerations. While particular examples of financial conditions are set forth herein for illustrative purposes, any embodiment 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.

[0233] The term interest rate and similar terms used herein should be understood broadly. Without limiting other aspects or descriptions of the present disclosure, interest rates include the amount of interest payable per period as a percentage of the loaned, deposited, or borrowed amount. The total interest on a loaned or borrowed amount may depend on the principal, the interest rate, the frequency of compounding, and the length of time the loan, deposit, or borrowed amount is outstanding. Interest rates are typically expressed as a yearly percentage, but can be defined for any period. Interest rates relate to the amount a bank or other lender charges to borrow its money or the interest rate a bank or other lender pays to savers to hold money in an account. Interest rates can be variable or fixed. For example, interest rates may vary according to government or other stakeholder mandates, the currency of the principal being lent or borrowed, the time to maturity of the investment, the borrower's perceived probability of default, market supply and demand, the amount of collateral, the state of the economy, or special features such as call clauses. In certain embodiments, interest rates may be relative interest rates (e.g., 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 does. Specific examples may not be interest rates for purposes of certain embodiments. For example, a bank account that grows by a fixed dollar amount each year and / or a fixed fee amount may not be examples of interest rates for certain embodiments. One skilled in the art with the benefit of the disclosure herein and knowledge of interest rates can readily determine the characteristics of interest rates for particular embodiments. Specific considerations for those skilled in the art regarding interest rates, or for embodiments of the present disclosure, include, but are not limited to, the currency of the principal, variables for setting the interest rate, criteria for adjusting the interest rate, the expected transaction type (loan, bond, or debt), the specific type of collateral, the loan-to-value ratio, the collateral-to-loan ratio, the total transaction / loan amount, the principal amount, the appropriate lifespan of the transaction and / or collateral for a particular industry, the likelihood that the lender will sell and / or consolidate the loan before the term, etc.While particular examples of interest rates are described herein for illustrative purposes, any embodiment 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, is specifically contemplated within the scope of this disclosure.

[0234] The term valuation service (and similar terms) as used herein should be understood broadly. Without limiting other aspects or descriptions of the present disclosure, a valuation service includes any service that sets a value for a good or service. A 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 output from a set of valuation services and allocate items of collateral sufficient to provide collateral for a loan and / or allocate value for items of collateral among a set of lenders and / or transactions. A valuation service may include an artificial intelligence service that may iteratively improve a valuation model based on outcome data related to collateral transactions. A valuation service may include a market value data collection service that monitors and reports market information related to the value of collateral. Certain processes may not be considered valuation services. For example, a point of sale (POS) that simply charges a set fee for a good or service may not be a valuation service. In another example, a service that tracks the cost of a good or service and triggers 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 applied in 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. A person 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 to combine processes and systems from the present disclosure to enhance the operation of the contemplated system and / or provide assessment services.To one of ordinary skill in the art, particular considerations in determining whether a contemplated system is a valuation service and / or whether aspects of the present disclosure may 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 smart contracts backed by collateral, revaluing collateral based on custody status or geolocation, the tendency of collateral to have volatile value, be utilized, and / or be moved, and the like. Specific examples of valuation services and considerations are described herein for illustrative purposes, however, any system that would benefit from the disclosure herein, and any consideration 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.

[0235] The term "collateral attributes" (and similar terms) as used herein should be understood broadly. Without being limited to other aspects or explanations of this disclosure, collateral attributes include any of the following: durability (the ability of the collateral to withstand wear or the useful life of the collateral), value, identification (whether the collateral has distinctive characteristics that make it easily identifiable or marketable), stability of value (whether the collateral maintains its value over time), standardization, grading, quality, marketability, liquidity, transferability, desirability, traceability, deliverability (whether the collateral can be delivered or transferred without deterioration in value), market transparency (whether the collateral's value is easily verifiable or widely agreed upon), physical or virtual, etc. Collateral attributes may be measured in absolute or relative terms and / or may include qualitative (e.g., categorical descriptions) or quantitative descriptions. Collateral attributes may vary by industry, product, element, application, etc. Collateral attributes can be assigned quantitative or qualitative values. Values ​​associated with collateral attributes may be based on a scale (e.g., 1 to 10) or a relative designation (e.g., high, low, good). Collateral can include various components, and each component can have collateral attributes. Thus, collateral may have multiple values ​​for the same collateral attribute. In some embodiments, multiple values ​​for collateral attributes can be combined to generate a single value for each attribute. Some collateral attributes may only apply to specific portions of the collateral. Some collateral attributes, even for a given component of the collateral, may have different values ​​depending on the stakeholders (e.g., a party that values ​​certain aspects of the collateral more highly than another party) and / or the type of transaction (e.g., collateral may be more valuable or appropriate for a first type of loan than a second type of loan). A particular attribute associated with collateral may not be a collateral attribute as described herein, depending on the purpose of the term collateral attribute herein.For example, a product may be rated as durable compared to similar products, but if the product's lifespan is much lower than the term of the particular loan under consideration, the product's durability may be rated differently (e.g., non-durable) or irrelevant (e.g., if current inventory of the product is attached as collateral and is expected to be replaced over the term of the loan). Accordingly, the benefits of the present disclosure may be applied to a variety of attributes, and any such attribute may be considered a collateral attribute herein, although 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 the contemplated collateral attributes typically available to him or her can readily determine which aspects of the present disclosure benefit particular collateral attributes. Particular considerations for one of ordinary skill in the art when determining whether a contemplated attribute is a collateral attribute and / or whether aspects of the present disclosure can benefit or enhance a contemplated system include, but are not limited to, the source of the attribute and the source of the attribute value (e.g., do the attribute and attribute value come from a trusted source?), the volatility of the attribute (e.g., do the collateral's attribute values ​​fluctuate or is the attribute a new attribute of the collateral?), the relative difference in the attribute value relative to similar collateral, exceptional values ​​for the attribute (e.g., an attribute value may be as high as the 98th percentile or very low as the 2nd percentile compared to collateral in a similar class), the liquidity of the collateral, the type of transaction related to the collateral, and / or the intended use of the collateral for a particular party or transaction. Specific examples of collateral attributes and considerations are described herein for illustrative purposes; however, any system benefiting from 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.

[0236] The term "blockchain service" (and similar terms) used herein should be understood broadly. Without limiting other aspects or descriptions of the present disclosure, a blockchain service may include any service related to processing, recording, and / or updating a blockchain, including services for processing blocks, calculating hash values, generating new blocks in a blockchain, and adding blocks to a blockchain. Examples include creating a fork of a blockchain, merging a fork of 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, and generating random numbers. Services may be performed by the execution of computer-readable instructions on a local computer and / or by remote servers and computers. Certain services may not be considered blockchain services individually, but may be considered blockchain services based on the end use of the service and / or in certain embodiments—for example, calculating a hash value may be performed in a context outside of a blockchain, such as in the context of secure communications. While some initial services may be invoked without first being applied to a blockchain, further actions or services in conjunction 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, and may be utilized by a blockchain, although they may not initially be generated for blockchain purposes. Accordingly, the benefits of the present disclosure may be applied in a wide variety of services, and any such service 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 with 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 provide benefits to a particular blockchain service. For those skilled in the art, particular 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., as noted below, some blockchain services may have an expected completion time and / or may be determined through utilization rates), the cost of the service, the amount of data required for the service, and / or the amount of data generated by the service (blocks on 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 that would benefit from the disclosure herein, and any considerations understood by a person skilled in the art with the benefit of the disclosure herein, are specifically contemplated within the scope of the present disclosure.

[0237] The term blockchain (and variants such as cryptocurrency ledger) as used herein may be broadly understood to describe a cryptocurrency ledger that records, manages, or otherwise processes online transactions. A blockchain may be public, private, or a combination thereof, without limitation. A blockchain may also be used to represent a series of digital transactions, agreements, terms, or other digital value. In the former case, a blockchain may also be used in connection with investment applications, token trading applications, and / or digital / cryptocurrency-based marketplaces, without limiting other aspects or descriptions of the present disclosure. A blockchain may also be associated with rendering consideration, such as the provision of goods, services, items, fees, access to restricted areas or events, data, or other valuable benefits. When discussing units of consideration, collateral, currency, cryptocurrency, or any other form of value, various forms of blockchain may be included. Those skilled in the art with the benefit of this disclosure and commonly available knowledge of the contemplated system can readily determine the value symbolized or represented by a blockchain. While particular examples of blockchains are described herein for illustrative purposes, any embodiment 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, is specifically contemplated within the scope of this disclosure.

[0238] The terms ledger and distributed ledger (and similar terms) used herein should be understood broadly. Without limiting other aspects or descriptions of the present 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 / decentralized. A centralized ledger may be a document managed, updated, or viewable by one or more selected entities or clearinghouses, with changes or updates to the ledger governed or managed by the entities or clearinghouses. A distributed ledger is a ledger distributed across multiple entities, participants, or geographies, and these entities can independently, simultaneously, or consensually update or modify their copies of the ledger. Ledgers and distributed ledgers may include security measures and cryptographic functions to sign, conceal, and verify content. In the case of distributed ledgers, blockchain technology may be used. In 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. Some transaction records may not be considered ledgers. Files, computer files, databases, and books may or may not be ledgers depending on the data they store, how the data is organized, maintained, and secured. For example, a list of transactions may not be considered a ledger if it cannot be trusted or verified and / or if it is based on inconsistent, fraudulent, or incomplete data. Ledger data may be organized in any format, such as tables, lists, or binary streams of data, depending on convenience, data source, data type, environment, application, etc.A ledger shared among various entities need not be a distributed ledger, although the distinction of distribution can be based on which entities are permitted to make changes to the ledger and / or how changes are shared and processed among different entities. Accordingly, the benefits of the present disclosure may apply to a wide variety of data, and any such data may be considered a ledger herein, while in certain embodiments, certain data may not be considered a ledger herein. Those skilled in the art, with the benefit of the disclosure herein and knowledge of contemplated ledgers and distributed ledgers generally available to them, can readily determine which aspects of the present disclosure can be utilized in an implementation and / or benefit a particular ledger. Particular considerations for those skilled in the art when determining whether contemplated data is a ledger and / or whether aspects of the present disclosure can 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 changed?), the time associated with making a change to the data in the ledger, the cost (computational and monetary) of making the change, details of the data, the composition of the data (whether the data needs to be processed for use in an application), who controls the ledger (is the party controlling the ledger trustworthy or reliable?), confidentiality of the data (who can see or track the data in the ledger?), size of the infrastructure, communication requirements (distributed ledgers may require communication interfaces or specific infrastructure), and resiliency. Specific examples of blockchain services and considerations are described herein for illustrative purposes; however, any system benefiting from 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.

[0239] The term loan (and similar terms) used herein should be understood broadly. Without limiting other aspects or descriptions of the present disclosure, a loan may be an agreement regarding assets borrowed and expected to be returned in kind (e.g., borrowed money and returned money) or in an agreed-upon transaction (e.g., a first good or service is borrowed and money, a second good or service, or a combination thereof). The asset may be money, property, time, a physical object, a virtual object, a service, a right (e.g., a ticket, license, or other right), an amortized amount, a credit (e.g., a tax credit, an emission credit, etc.), an agreed-upon assumption of risk or responsibility, and / or any combination thereof. A loan is made based on a formal or informal agreement between a borrower and a lender, and the lender may provide the asset to the borrower for a predefined period, a variable period, or an indefinite period. The lender and borrower may be individuals, entities, corporations, governments, groups, organizations, etc. Types of loans may include mortgages, personal loans, secured loans, unsecured loans, concession loans, commercial loans, microloans, etc. An agreement between a borrower and a lender may specify the terms of the loan. The borrower may be required to return an asset or repay with an asset different from the loan. In some cases, repayment may be required with interest on the borrowed asset. The borrower and lender may be intermediaries between other entities and may not own or use the asset. In some embodiments, a loan may not involve the direct transfer of an item, but rather a right of use or a shared right of use. In certain embodiments, an agreement between a borrower and a lender may be executed between the borrower and lender and / or between an intermediary (e.g., a beneficiary of the loan interest, such as through the sale of the loan). In certain embodiments, the contract between the borrower and lender may be executed through a service herein, such as a smart contract service, which may be a smart contract 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.In certain embodiments, the smart contract service may input the terms of the agreement and present them 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, for example, if the set of loans includes multiple beneficiaries of payments on the set of loans and / or multiple borrowers for the set of loans. In certain embodiments, the risk and / or obligations of the set of loans may be individualized (e.g., each borrower and / or lender is associated with a particular loan in 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 are treated and / or allocated separately).

[0240] Certain agreements may not be considered loans. Agreements to transfer or borrow assets may not be loans, depending on the assets transferred, how the assets are transferred, and the parties involved. For example, an asset transfer may occur for an indefinite period and be considered a sale or permanent transfer of the assets. Similarly, an asset borrowing or transfer without clear terms or agreements between the lender and borrower may not be considered a loan, depending on the circumstances. Even if a formal agreement is not directly codified in a contract, an agreement may be considered a loan as long as the parties willingly and knowingly agree to the arrangement and / or because common practice (e.g., in a particular industry) would treat the transaction as a loan. Thus, the benefits of this disclosure may be applicable to a wide variety of agreements, and any such agreement may be considered a loan herein, although in certain embodiments, a given agreement may not be considered a loan herein. One of ordinary skill in the art, with the benefit of the disclosure herein and knowledge of contemplated loans typically available to them, can readily determine which aspects of this disclosure are beneficial to making a loan, utilizing a loan, or a particular loan transaction. Particular considerations for one of ordinary skill in the art when determining whether a contemplated data is a loan and / or whether aspects of the present disclosure can benefit or enhance a contemplated loan include, but are not limited to, the value of the assets involved, the borrower's ability to return or repay the loan, the type of asset involved (e.g., whether the asset is consumed by use), the repayment period associated with the loan, the interest rate on the loan, how the loan agreement was arranged, the form of the agreement, the details of the agreement, the details of the loan agreement, collateral attributes associated with the loan, and / or normal business expectations of any of the foregoing in the particular context. While particular examples of loans and considerations are described herein for illustrative purposes, any system benefiting from the disclosures herein, and any considerations understood by one of ordinary skill in the art with the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.

[0241] As used herein, the terms "loan-related event(s)" (and similar terms including "loan-related events") should be understood broadly. Without being limited to other aspects or descriptions of the present disclosure, a loan-related event may include any 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 breach of contract, performance, repayment, payment, interest change, late fee assessment, refund assessment, distribution, etc. A loan-related event may also be triggered by explicit contract terms. For example, a contract may specify an interest rate increase after a certain period of time has passed since the origination of the loan, and an interest rate increase triggered by the contract may be a loan-related event. A loan-related event may also be implicitly caused by the relevant loan contract clause. In certain embodiments, any occurrence considered relevant to the assumptions of the loan contract and / or the expectations of the parties to the loan contract may be considered an occurrence of an event. For example, if 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 a loan-related event. In another example, when a review and / or verification of the collateral is expected, a lack of access to the collateral, a disabled or failed monitoring sensor, etc. may be considered the occurrence of a loan-related event. In certain embodiments, the circuitry, controller, or other device 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 needs to be completed by the lender, borrower, or a third party. 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 associated with a loan, but may be caused by external triggers that are not associated with a loan.However, in certain embodiments, an external triggering event (e.g., a commodity price change related to the collateral) may also 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. Accordingly, the benefits of the present disclosure may be applied in a wide variety of events, and while any such event may be considered a loan-related event herein, in certain embodiments, certain events may not be considered loan-related events herein. Those skilled in the art with the benefit of the disclosure herein and knowledge of the contemplated systems generally available to them can readily determine which aspects of the present disclosure may be considered loan-related events for the contemplated systems and / or particular transactions supported by the systems. To those skilled in the art, particular considerations in determining whether contemplated data is a loan-related event and / or whether aspects of the present disclosure may benefit a contemplated trading system include, but are not limited to, the impact of the related event on the loan (an event that causes 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 duration and / or response time associated with the event (e.g., the time required to complete the event, the time allotted from the time the event is triggered to the time the event is desired to be processed or detected), the entity responsible for the event, the data required to process the event (e.g., confidential information may have different safeguards or restrictions), the availability of mitigation measures in the event of an undetected event, and / or the remedies available to the at-risk party in the event of an undetected event. While specific examples of loan-related events and considerations are described herein for illustrative purposes, any system 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.

[0242] The term "loan-related activities" (and similar terms) used herein should be broadly understood. Without limiting other aspects or descriptions of this disclosure, loan-related activities may include activities related to loan origination, maintenance, termination, collection, enforcement, servicing, billing, marketing, performance, or negotiation. Loan-related activities may include activities related to the signing of a loan agreement or promissory note, review of loan documents, processing payments, valuation of collateral, evaluation of a borrower's or lender's compliance with 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 before the terms are formally agreed upon, such as activities related to initial negotiations. Loan-related activities may relate to events during the loan term and after the loan's closing. Loan-related activities may be conducted by the lender, the borrower, or a third party. For example, invoicing for a loan balance is considered loan-related activity, but if invoicing for a loan is combined with invoicing for non-loan-related elements, the invoicing may not be considered loan-related activity. Certain activities may occur in connection with an asset regardless of whether a loan is associated with the asset, and in such cases, the activity may not be considered loan-related activity. For example, a periodic audit related to an asset may occur regardless of whether the asset is associated with 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 if not associated with the loan, in which case the activity may be considered loan-related activity. In some embodiments, an activity may be considered loan-related activity if it would not otherwise occur if the loan is inactive or nonexistent, but may still be considered loan-related activity in some cases (e.g., if an audit normally occurs but the lender does not have the ability to conduct or review the audit, the audit may be considered loan-related activity even if it would otherwise have already occurred).Thus, the benefits of the present disclosure may be applied in a wide variety of events, and any such event may be considered a loan-related event herein, while in certain embodiments, certain events may not be considered loan-related events herein. A person skilled in the art with the benefit of the disclosure herein and knowledge of the contemplated system generally available to him or her can readily determine loan-related activity for purposes of the contemplated system. Particular considerations for a person skilled in the art when determining whether contemplated data is loan-related activity and / or whether aspects of the present disclosure can benefit or enhance a contemplated loan include, but are not limited to, the following: the necessity of the activity to the loan (the loan agreement or terms can be met without the activity), the cost of the activity, the specificity of the activity to the loan (is the activity similar or identical to other industries?), the time involved in the activity, the impact of the activity on the loan's life cycle, 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 loan-related events and considerations 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 this disclosure.

[0243] As used herein, terms such as loan terms, loan terms, terms for a loan, and conditions should be broadly understood ("Loan Terms"). Without limiting other aspects or descriptions of this disclosure, loan terms may relate to conditions, rules, restrictions, contractual obligations, etc. related to timing, repayment, composition, and other enforceable terms agreed upon by a borrower and a loan lender. Loan terms may be specified in a formal agreement between a borrower and a lender. Loan terms may specify aspects such as interest rates, collateral, foreclosure terms, debt consequences, payment methods, payment schedules, and covenants. Loan terms are negotiable and may change during the life of the loan. Loan terms may change or be influenced by external parameters such as market prices, bond prices, and terms related to the lender or borrower. 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 a lender and a borrower and / or that are not commonly understood in the course of business (and / or a particular industry) may not be considered loan terms. Some aspects of a loan may be preliminary or informal until formally confirmed in a contract or formal agreement. Some 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. Some aspects of a loan may not be considered loan conditions at a particular time during the loan, but may be considered loan conditions at another time during the loan (e.g., obligations and / or waivers that may arise through the parties' performance and / or the expiration of the loan term). For example, an interest rate is generally defined in the loan context and may not be considered a loan condition until it is defined in terms of interest compounding (yearly, monthly), calculation method, etc. An aspect of a loan may not be considered a term if it is indefinite or unenforceable. Some aspects may be manifestations of or related to the term of a loan, but may not be a term in itself. For example, a loan term may be the repayment period of the loan, such as one year. The terms may not specify how the loan is repaid within that year. The loan may be repaid in 12 monthly payments or in one year.The monthly payment plan in this case may not be considered a loan term, as it may simply be one option or many options for repayment not directly specified by the loan. Thus, the benefits of the present disclosure may be applied to a wide variety of loan aspects, and any such aspect may be considered a loan term herein, although in certain embodiments certain aspects may not be considered a loan term herein. One of ordinary skill in the art with 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 are loan terms of the contemplated systems.

[0244] Particular considerations for one of ordinary skill in the art when determining whether contemplated data are loan terms and / or whether aspects of the present disclosure may benefit or enhance the contemplated loan include, but are not limited to, the enforceability of the terms (can the lender or borrower enforce the terms?), the cost of enforcing the terms (the amount of time or effort required to ensure 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?), the entity responsible for the terms, the fairness of the terms, the stability of the terms (how often they change?), the observability of the terms (can other parties verify the terms?), the favorability of the terms to one party (whether favoring the borrower or lender?), the risks associated with the loan (the terms may depend on the likelihood that the loan will not be repaid?), the characteristics of the borrower and lender (their ability to meet the terms?), and / or normal expectations for the lending or related industry.

[0245] While specific examples of loan terms 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 expressly contemplated within the scope of this disclosure.

[0246] As used herein, terms such as loan terms, loan conditions, terms for a loan, and conditions should be understood broadly ("loan terms"). Without limiting other aspects or descriptions of the present disclosure, loan terms may relate to rules, restrictions, and / or obligations associated with a loan. Loan terms may relate to rules or required obligations for obtaining a loan, maintaining a loan, applying for a loan, or transferring a loan. Loan terms may include the principal amount of the debt, the outstanding debt, fixed interest rate, variable 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, term, agreement, foreclosure conditions, default conditions, conditions regarding the borrower's other obligations, consequences of default, etc.

[0247] 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 a particular industry) may not be considered loan conditions. Certain aspects of a loan may be preliminary and informal until formally agreed upon 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 the loan, but may be considered loan conditions at another time during the loan (e.g., obligations and / or waivers that may arise through the parties' performance and / or expiration of a loan condition). Thus, the benefits of the present disclosure may be applicable to a wide variety of loan aspects, and any such aspect may be considered a loan condition herein, although in certain embodiments, certain aspects may not be considered loan conditions herein. A person of ordinary skill in the art with the benefit of the disclosure herein and knowledge of the contemplated systems generally available to him or her can readily determine which aspects of the present disclosure are loan terms of the contemplated systems. Particular considerations for the person of ordinary skill in the art when determining whether contemplated data is a loan term and / or whether aspects of the present disclosure may benefit or enhance a contemplated loan include, but are not limited to, the following:the enforceability of the condition (can the condition be enforced by the lender or the borrower), the cost of enforcing the condition (the amount of time or effort required to ensure that the condition is adhered to), the complexity of the condition (how easily the parties can adhere to it / understand it / are the conditions prone to error / misinterpretation), who is responsible for the condition, ...

[0248] While specific examples of loan terms 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 expressly contemplated within the scope of this disclosure.

[0249] The terms loan collateral, pledge, collateral, and similar terms used herein should be understood broadly. Without limiting other aspects or descriptions of the present disclosure, loan collateral may refer to any asset or property that a borrower pledges to a lender as backup and / or security for a loan. Collateral may be any item of value that is accepted as an alternative form of repayment in the event of a loan default. Collateral may include any number of physical or virtual items, such as vehicles, 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, intellectual property, intellectual property rights, contractual rights, antiques, fixtures, furniture, equipment, tools, machinery, and personal property. Collateral may include multiple items or types of items.

[0250] A collateral item may represent an asset, property, value, or other item defined as collateral for a loan or transaction. A set of collateral items may be defined, and the substitution, removal, or addition of a collateral item within the set may be affected. For example, a collateral item may be, but is not limited to, a vehicle, a vessel, an aircraft, a building, a home, real estate, undeveloped land, a farm, crops, municipal facilities, a warehouse, inventory, merchandise, securities, currency, negotiable instruments, tickets, cryptocurrency, consumables, food, beverages, precious metals, or jewelry. Items such as precious metals, jewelry, gemstones, intellectual property, contractual rights, antiques, fixtures, furniture, equipment, tools, machinery, or personal property may be affected. When a set or plurality of collateral items is defined, the substitution, removal, or addition of a collateral item to or from the set of collateral items may be affected. Without limiting other aspects or descriptions of this disclosure, a collateral item or set of collateral items may also be used in conjunction with other terms of a contract or loan, such as representations, warranties, indemnities, covenants, outstanding debt, fixed interest rates, variable interest rates, payment amounts, etc. It is used in conjunction with other terms of the agreement or loan, such as variable interest rates, payment amounts, payment schedules, balloon payment schedules, collateral designations, collateral fungibility designations, collateral, personal guarantees, liens, terms, foreclosure conditions, default conditions, and default consequences. In certain embodiments, the smart contract may calculate whether the borrower has met the conditions or terms, and if the borrower has not met such conditions or terms, it may enable automated action, trigger another condition or term that may affect the status, ownership, or transfer of the collateral item, or initiate the substitution, removal, or addition of a collateral item to the collateral set for the loan. Those skilled in the art, having the benefit of this disclosure and knowledge of collateral, can readily determine the purpose and use of collateral (including its substitution, removal, and addition) in the various embodiments and contexts disclosed herein.

[0251] Although the specific example of loan collateral is described herein for purposes of illustration, 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, is expressly contemplated within the scope of this disclosure.

[0252] The term "smart contract service" (and similar terms) used herein should be understood broadly. Without limiting 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 agreement. For example, a smart contract service may specify the terms of a smart contract, such as in a rules database, or process outputs from a set of evaluation services and allocate sufficient items of collateral to provide collateral for a loan. A smart contract service may automatically execute a set of rules or conditions embodying a smart contract, and the execution may be based on or utilize collected data. A smart contract service may configure a smart contract to automatically initiate a loan payment request, automatically initiate a foreclosure process, automatically initiate an action to claim replacement or backup collateral or transfer ownership of collateral, automatically initiate an inspection process, automatically modify payment or interest terms based on collateral, and automatically undertake loan-related actions. The smart contract may govern 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 can facilitate, verify, or enforce the negotiation or execution 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.

[0253] A process 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 applied in a wide variety of process systems, and any such process or system may be considered a smart contract or smart contract service herein, although in certain embodiments a given service may not be considered a smart contract service herein.

[0254] A person of ordinary skill in the art with the benefit of the disclosure herein and knowledge of the contemplated systems generally available to them will be readily able to 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 implement a smart contract service and / or enhance the operation of a contemplated system. Particular considerations for a person of ordinary skill in the art when determining whether a contemplated system includes a smart contract service or smart contracts and / or whether aspects of the present disclosure may benefit a contemplated system include, but are not limited to, the following: These include the ability to automatically transfer ownership of collateral in response to an event, automated actions available upon discovery of covenant compliance (or lack thereof), amenability to collateral clustering, rebalancing, allocation, addition, replacement, and removal of items from collateral, modification parameters of aspects of the loan in response to an event (e.g., timing, complexity, suitability for loan type, etc.), complexity of the loan terms for the system, including benefit from rapid determination and / or prediction of changes in entities related to the loan (e.g., collateral, financial condition of the parties, offsetting collateral, and / or industry related to the parties), suitability of automated generation of terms and / or condition execution for the type of loan, party, and / or industry contemplated for the system, etc. While specific examples of smart contract services and considerations are described herein for illustrative purposes, any system benefiting from 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.

[0255] The term IoT system (and similar terms) as used herein should be understood broadly. Without limiting other aspects or descriptions of the present 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. While certain components may not individually be considered an IoT system, in an aggregated system—e.g., a single networked system—they may be considered an IoT system.

[0256] A sensor, smart speaker, and / or medical device may not be an IoT system, but may be part of a larger system and / or may be considered an IoT system and / or part of an IoT system in the aggregate with many other similar components. In certain embodiments, a system may be considered an IoT system for some purposes but not for 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, locally networked source. Furthermore, in certain embodiments, otherwise similar-appearing systems may be distinguished when determining whether and / or what type of IoT system such a system is. For example, one group of medical devices may not share to an aggregated HER database at one time, while another group of medical devices may share data to an aggregated HER for clinical research purposes; accordingly, one group of medical devices may be an IoT system, while the other group may not. Thus, the benefits of the present disclosure may be applied in a wide variety of systems, and while any such system may be considered an IoT system herein, in certain embodiments, a given system may not be considered an IoT system herein. A person of ordinary skill in the art with the benefit of the disclosure herein and knowledge of the contemplated system generally available to him or her can readily determine which aspects of the present disclosure will benefit a particular system, how to combine processes and systems from the present disclosure to enhance the operation of the contemplated system, and what circuits, controllers, and / or devices comprise the IoT system of the contemplated system.Particular considerations for one of ordinary skill in the art when determining whether a contemplated system is an IoT system and / or whether aspects of the present disclosure may benefit or enhance the contemplated system include, but are not limited to, the system's transmission environment (e.g., low power, availability of device-to-device networking), shared data storage for devices, establishment of geofences by devices, service as a blockchain node, asset, collateral, or entity monitoring capabilities, relaying data between devices, ability to aggregate data from multiple sensors or monitoring devices, and the like. While particular examples of IoT systems and considerations are described herein for illustrative purposes, any system that would benefit 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.

[0257] The term data collection service (and similar terms) as used herein should be understood broadly. Without limiting other aspects or descriptions of the present disclosure, a data collection service includes any service that collects data or information, including any circuit, 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, such as to identify data or information for collection. A data collection service may be event-driven, run periodically, or obtain data from an application at a specific point during the application's execution. 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 networked 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 in a wide variety of process systems, and any such process or system may be considered a data collection service herein, although in certain embodiments, a given service may not be considered a data collection service herein. A person of ordinary skill in the art with the benefit of the disclosure herein and knowledge of the contemplated systems generally 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 implement a data collection service and / or enhance the operation of a contemplated system. Particular considerations for a person of ordinary skill in the art when determining whether a contemplated system is a data collection service and / or whether aspects of the present disclosure can benefit or enhance a contemplated system include, but are not limited to, the following:These include the ability to modify business rules on the fly and change 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 networked points of sale, needing data from one or more distributed sensors or cameras, and the like. While specific examples of data collection services and considerations 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.

[0258] The term data integration service (and similar terms) as used herein should be understood broadly. Without limiting 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 may extract, transform, load, normalize, compress, decompress, encode, decode, and otherwise process data packets, signals, and other information. A data integration service may monitor entities 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. Accordingly, the benefits of the present disclosure may be applied in a wide variety of process systems, and any such process or system may be considered a data integration service herein, while in certain embodiments, a given service may not be considered a data integration 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 can readily determine which aspects of the present disclosure will benefit a particular system and how to combine processes and systems from the present disclosure to implement a data integration service and / or enhance the operation of the contemplated system. For those skilled in the art, particular considerations in determining whether a contemplated system is a data integration service and / or whether aspects of the present disclosure could benefit a contemplated system include, but are not limited to, the ability to modify business rules on the fly and change data integration protocols, communication with third-party databases to bring in data to be integrated, synchronization of data across disparate platforms, connection to a central data warehouse, data storage capacity, processing capacity, and / or communication capacity distributed across the system, connection of separate automated workflows, and the like. Specific examples of data integration services and considerations are described herein for illustrative purposes, but any system that would benefit from the disclosure herein, and any considerations that would be understood by one of skill in the art with the benefit of the disclosure herein, are specifically contemplated within the scope of the present disclosure.

[0259] The term "computational service" (and similar terms) as used herein should be understood broadly. Without limiting 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 a blockchain service, a data collection service, a data integration service, an evaluation service, a smart contract service, a data monitoring service, data mining, and / or any service that facilitates 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, while the benefits of the present disclosure may be applicable in a wide variety of process systems, and any such process or system may be considered a computational service herein, in certain embodiments, a given service may not be considered a computational service herein. Those skilled in the art, with the benefit of the disclosure herein and knowledge of contemplated systems typically available to them, will be able to readily determine which aspects of the present disclosure will benefit a particular system and how to combine processes and systems from the present disclosure to implement one or more computational services and / or to enhance the operation of a contemplated system. Particular considerations for those skilled in the art when determining whether a contemplated system is a computational service and / or whether aspects of the present disclosure could benefit or enhance a contemplated system include, but are not limited to, achieving one or more of: agreement-based access to services; brokering exchanges between different services; providing on-demand computational power to web services; and monitoring, collecting, accessing, processing, transforming, analyzing, storing, integrating, visualizing, mining, or sharing data. Specific examples of computational services and considerations are described herein for illustrative purposes; however, any system that would benefit from the disclosure herein, and any consideration that would be understood by one skilled in the art with the benefit of the disclosure herein, is specifically contemplated within the scope of the present disclosure.

[0260] The term sensor as used herein should be understood broadly. Without limiting 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 sensor may record, indicate, transmit, or otherwise respond to the detection or measurement. Examples of sensors may be sensors for sensing the movement of an entity, sensors for sensing temperature, pressure, or other attributes related to the entity or its environment, cameras that capture still or moving images of an entity, and sensors that collect data related to collateral or assets, such as location, condition (health, physical, or other), quality, security, ownership, or the like. In embodiments, a sensor may be sensitive to the characteristic being measured but insensitive to or unaffected by other characteristics. A sensor may be analog or digital. A sensor may include a processor, a transmitter, a transceiver, a memory, power, sensing circuitry, an electrochemical fluid reservoir, a light source, etc. Further examples of sensors contemplated for use in the system include biosensors, chemical sensors, black silicon sensors, IR 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, 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 sensors, metal detectors, rain sensors, altimeters, GPS, outdoor detection, context detection, activity detection, object detection (e.g., collateral), and marker detection. These include sensors such as collateral, marker detectors (such as geolocation markers), laser range finders, sonar, capacitance, optical response, heart rate sensors, or RF / micropower impulse radio (MIR) sensors.In certain embodiments, a sensor may be a virtual sensor—e.g., determining a parameter of interest as a calculation based on other sensed parameters in the system. In certain embodiments, a sensor may be a smart sensor—e.g., reporting a sensed value as an abstracted communication (e.g., as a network communication). In certain embodiments, a sensor may provide a sensed value directly (e.g., as a voltage level, frequency parameter, etc.) to a circuit, controller, or other device in the system. 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 from a sensor. Particular considerations for one of ordinary skill in the art when determining whether a contemplated device is a sensor and / or whether aspects of the present disclosure could benefit from or be enhanced by a contemplated sensor include, but are not limited to, coordinating system activation / deactivation with environmental quality, converting electrical output to a measurement, the ability to enforce geofencing, automatic loan modifications in response to changes in collateral, and the like. While specific examples of sensors and considerations 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.

[0261] The term "storage conditions" and similar terms used herein should be understood broadly. Without limiting other aspects or descriptions of the present disclosure, storage conditions include the environment, physical location, environmental quality, exposure levels, security measures, maintenance instructions, accessibility instructions, and the like, related to the storage of assets, collateral, or entities specified and monitored in a contract, loan, or agreement, or in support of a contract, loan, or other 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 its use as collateral. Based on the storage condition, measures 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 or on data from Internet of Things devices, data from a set of environmental condition sensors, a social network analysis service and a set of algorithms querying network domains, social media data, crowdsourced data, etc. Storage conditions may be tied to geographic locations associated with the collateral, issuer, borrower, distribution of funds, or other geographic locations. Examples of IoT data may include images, sensor data, location information, etc. Examples of social media data or crowdsourced data may include the actions of parties to a loan, the financial status of parties, parties' compliance with the terms of a loan or bond, or the like. Parties to a loan may include the bond issuer, related entities, lenders, borrowers, and third parties with an interest in the debt. Storage terms may relate to asset or collateral types, such as municipal assets, vehicles, vessels, airplanes, buildings, homes, real estate, undeveloped land, farms, crops, municipal facilities, warehouses, inventory, merchandise, securities, currency, securities, tickets, cryptocurrencies, consumables, foodstuffs, beverages, precious metals, jewelry, gemstones, intellectual property rights, contractual rights, antiques, fixtures, furniture, equipment, tools, machinery, and personal property.The custody state 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 custody state of a collateral, asset, or entity may include managing, reporting, modifying, syndicating, consolidating, terminating, maintaining, terms and / or amending, asset seizure, or other disposition of a loan, contract, or agreement. Those skilled in the art with the benefit of this disclosure and knowledge of the contemplated custody conditions can readily determine which aspects of this disclosure will benefit a particular application of the custody conditions. Particular considerations for those skilled in the art when selecting appropriate custody conditions to manage and / or monitor, or for embodiments of the present disclosure, include, but are not limited to, the legality of the terms given the jurisdiction of the transaction, the available data for the given collateral, the expected type of transaction (loan, bond, or debt), the particular type of collateral, the loan-to-value ratio, the collateral-to-loan ratio, the total transaction / loan amount, the credit scores of the borrower and lender, common practices in the industry, and other considerations. While specific examples of storage conditions are set forth herein for illustrative purposes, any embodiment having the benefit of this disclosure, and any considerations that would be understood by one of ordinary skill in the art having the benefit of this disclosure, is specifically contemplated within the scope of this disclosure.

[0262] The term geolocation and similar terms used herein should be understood broadly. Without limiting other aspects or descriptions of the present disclosure, geolocation includes identifying or estimating the real-world geographic location of an object, including generating a set of geographic coordinates (e.g., latitude and longitude) and / or an 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 its use as collateral. Based on the geolocation, steps may be taken to modify the terms of a loan or bond. Based on geolocation, decisions or predictions regarding transactions may be made based on, for example, weather, local civil unrest, 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 social network analysis service and a set of algorithms for querying network domains, social media data, crowdsourcing data, etc. Examples of geolocation data may include GPS coordinates, images, sensor data, addresses, etc. Geolocation data may be quantitative (e.g., longitude / latitude, relative to a flat map, etc.) and / or qualitative (e.g., categories such as “coastal,” “rural,” etc., “within 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 data or crowdsourced data may include the behavior of a party to a loan as inferred by geolocation, a party’s financial status as inferred by geolocation, a party’s compliance with the terms or provisions of a loan or bond, or the like. Geolocation may be determined for assets or types of collateral, such as municipal assets, vehicles, vessels, airplanes, buildings, homes, real estate, undeveloped land, farms, crops, municipal facilities, warehouses, inventory, merchandise, securities, etc.Currency, securities, tickets, consumables, food, beverages, precious metals, jewelry, gemstones, antiques, fixtures, furniture, equipment, tools, machinery, and personal items. Geolocation may be determined for entities such as one of the parties, a third party (e.g., an inspection service, maintenance service, cleaning service, etc. related to the transaction), or other entities related to the transaction. Geolocation may also include environments selected from among a municipal environment, a business 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 geolocation of collateral, assets, or entities may include managing, reporting, modifying, syndicating, consolidating, terminating, maintaining, modifying terms and / or amending, foreclosing on assets, or other dispositions of loans, contracts, or agreements. Those skilled in the art with the benefit of this disclosure 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 an item's location constitute geolocation for the contemplated system. Specific considerations to one of ordinary skill in the art, or to embodiments of the present disclosure, when selecting an appropriate geolocation to manage include, but are not limited to, the legality of the geolocation given the jurisdiction of the transaction, the data available for the given collateral, the expected transaction type (loan, bond, or debt), the particular type of collateral, the loan-to-value ratio, the collateral-to-loan ratio, the total transaction / loan amount, the borrower's frequency of travel to the particular jurisdiction and other considerations, the 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 relevant services, etc.). While specific examples of geolocations are described herein for illustrative purposes, any embodiment benefiting from this disclosure, and any considerations understood by one of ordinary skill in the art having the benefit of this disclosure, are specifically contemplated within the scope of the present disclosure.

[0263] The term jurisdiction and similar terms as used herein should be understood broadly. Without being limited to other aspects or descriptions of the present disclosure, jurisdiction refers to the laws and legal authority that govern a loan entity. 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 country of incorporation of a company, etc.), the country of grant of certain rights such as intellectual rights, etc. In certain embodiments, jurisdictional location may be one or more of the geolocations of entities within the system. In certain embodiments, jurisdictional location may not be the same as the geolocation of any entity within the system (e.g., if the contract specifies some other jurisdiction). In certain embodiments, jurisdictional location may differ for entities within the system (e.g., the borrower is in A, the lender is in B, the collateral is in C, the contract is enforced in D, etc.). In certain embodiments, jurisdictional location for a given entity may change during operation of the system (e.g., due to movement of collateral, related data, changes in terms, etc.). In certain embodiments, a given entity in the system may have more than one jurisdiction (e.g., due to the operation of relevant law and / or options available to one or more parties) and / or may have different jurisdictions for different purposes. The jurisdictional location of a collateral item, asset, or entity, or action may dictate certain terms or provisions of a loan or bond and / or may indicate different obligations regarding notice to parties, foreclosure and / or enforcement of default, handling of collateral and / or debt instruments, and handling of various data within the system. While specific examples of jurisdictional locations are described herein for illustrative purposes, any embodiment benefiting from the disclosure herein, and any considerations understood by those skilled in the art with the benefit of the disclosure herein, are specifically contemplated within the scope of the present disclosure.

[0264] As used herein in the context of increments of value, variations such as token of value, token, and cryptocurrency token may be used to represent either (A) a unit of currency or cryptocurrency (e.g., a cryptocurrency token) or (b) a credential exchangeable for goods, services, data, or other valuable consideration (e.g., a token of value), and may be broadly understood to refer to either. Without limiting other aspects or descriptions of this disclosure, in the former case, tokens may also be used in conjunction with investment applications, token trading applications, and token-based marketplaces. In the latter case, tokens may also be associated with rendering 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, tokens of value can be exchanged for accommodations (e.g., hotel rooms), food / dining products and services, space (e.g., shared spaces, workspaces, convention spaces, etc.), fitness / wellness products or services, event tickets or admission to events, travel, flights or other transportation, digital content, virtual goods, license keys, or other valuable goods, services, data, or consideration. Various forms of tokens 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 skilled in the art with the benefit of this disclosure and knowledge of tokens can readily determine the value symbolized or represented by a token, whether currency, cryptocurrency, goods, services, data, or other value. While specific examples of tokens are described herein for illustrative purposes, any embodiment benefiting from this disclosure, and any considerations understood by those skilled in the art with the benefit of this disclosure, are specifically contemplated within the scope of this disclosure.

[0265] The term pricing data, as used herein, may be broadly understood to describe an amount of information, such as the price or cost, of one or more items in a market. Without limiting other aspects or descriptions of the present disclosure, pricing data may also be used in conjunction 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 and facility data, labor data, event data, underwriting data, claims data, or other forms of data. Pricing data may be tailored to the context (e.g., condition, liquidity, location, etc.) of the item being valued and / or the context of a particular party. One of ordinary skill in the art with the benefit of this disclosure and knowledge of pricing data can readily determine the purpose and use of pricing data in the various embodiments and contexts disclosed herein.

[0266] Without limiting other aspects or descriptions of the present disclosure, a token includes, without limitation, any token of value, such as collateral, an asset, a reward, or the like, or a token that serves as a representation of value, such as a value-holding voucher redeemable for goods or services. Certain components may not be considered tokens individually, but may be considered tokens in an aggregated system—e.g., value placed on an asset may not itself be a token, but the asset's value may be placed in 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, where the value attributed to the token is stored on the blockchain circuit's distributed ledger, but the value-assigned token itself can be exchanged or traded, such as through a token marketplace. In certain embodiments, a token may be considered a token for some purposes but not for other purposes—e.g., a token may be used as a representation of ownership of an asset, but this use of the token would not be traded as value, where a token containing the value of the asset might be. Thus, the benefits of the present disclosure may be applied in a wide variety of systems, and any such system may be considered a token herein, although in certain embodiments, a given system may not be considered a token herein. A person of ordinary skill in the art with the benefit of the disclosure herein and knowledge of the contemplated systems typically available to them will readily be able to determine which aspects of the present disclosure will benefit a particular system and / or how processes and systems from the present disclosure may be combined to enhance the operation of a contemplated system.For those skilled in the art, particular considerations 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 related to access rights, tickets, and tokens, use in investment applications such as investing in stocks, equity, and tokens, token trading applications, token-based marketplaces, forms of consideration such as monetary compensation and tokens, conversion of the value of resources in tokens, indications of ownership such as cryptocurrency tokens, identity information, event information, and token information, blockchain-based access tokens traded in marketplace applications, pricing applications such as for setting and monitoring prices for associated access rights, underlying access rights, tokens, and fees, trading applications for trading or exchanging associated access rights or underlying access rights or tokens, tokens (e.g., tickets) created and stored on a blockchain for associated access rights that carry ownership rights, etc.

[0267] The term financial data, as used herein, may be broadly understood to refer to a collection of financial information regarding assets, collateral, or other items. Financial data may include revenues, expenses, assets, liabilities, capital, bond ratings, defaults, return on assets (ROA), return on investment (ROI), past performance, expected future performance, earnings per share (EPS), internal rate of return (IRR), earnings announcements, ratios, statistical analyses of any of the foregoing (e.g., moving averages), and the like. Without limiting other aspects or descriptions of the present disclosure, financial data may also be used in conjunction with pricing data and market value data. Financial data may satisfy one or more conditions or trigger the application of one or more rules of a smart contract. 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, labor data, event data, underwriting data, claims data, or other forms of data. Those skilled in the art with the benefit of this disclosure and knowledge of financial data can readily determine the purpose and use of pricing data in the various embodiments and contexts disclosed herein.

[0268] The term covenant, as used herein, may be broadly understood to refer to a condition, agreement, or promise, such as the performance of a certain act or omission. For example, a covenant may relate to a party's conduct or legal status. Without being limited to other aspects or explanations of this disclosure, covenant may also be used in combination with other terms related to contracts or loans, such as representation, warranty, indemnity, outstanding debt, fixed interest rate, variable interest rate, payment amount, payment schedule, and payment terms. Terms such as payment amount, payment schedule, balloon payment schedule, collateral designation, collateral fungibility designation, parties, guarantee, guarantor, collateral, personal guarantee, lien, term, foreclosure condition, default condition, and default consequence may be used. A breach of a covenant or a promise may satisfy one or more conditions or trigger a recovery, breach, or other condition. In certain embodiments, a smart contract may calculate whether a covenant has been satisfied and, if a covenant has not been satisfied, enable automated action or trigger other conditions or clauses. Those skilled in the art with the benefit of this disclosure and knowledge of the covenants can readily determine the purpose and use of the covenants in the various embodiments and contexts disclosed herein.

[0269] The term entity, as used herein, may be broadly understood to refer to an identifiable related object, such as a party, a third party (e.g., an auditor, a regulator, a service provider, etc.), and / or a collateral item related to a transaction. Exemplary entities include individuals, partnerships, corporations, limited liability companies, or other legal organizations. Other exemplary entities include identifiable items of collateral, 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 as having 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 an agent representing or acting on behalf of the entity. Without being limited to other aspects or descriptions of the present disclosure, an entity may also be used in conjunction with other related entities or terms of a contract or loan: for example, representations, warranties, indemnities, agreements, debt balances, fixed interest rates, floating interest rates, payment amounts, payment schedules, payment schedules, payment schedules, etc. The attributes of an entity may include, but are not limited to, payment amounts, payment schedules, balloon payment schedules, collateral designations, collateral fungibility designations, parties, guarantees, sureties, collateral, personal guarantees, liens, terms, foreclosure conditions, default conditions, and default consequences. An entity may have a set of attributes, such as, but not limited to, published valuation, the set of property owned by the entity as shown by public records, the valuation of the set of property owned by the entity, bankruptcy status, foreclosure status, contractual default status, regulatory violation status, criminal status, export control status, embargo status, tariff status, export control status, embargo status, tariff status, tax status, credit report, credit rating, website rating, a set of customer reviews for the entity's products, social network ratings, a set of credentials, a set of referrals, a set of testimonials, a set of behaviors, location, and geolocation.In certain embodiments, a smart contract may calculate whether an entity has met a condition or covenant, and may enable automated actions or trigger other conditions or clauses if the entity has not met such condition or covenant. One of ordinary skill in the art with the benefit of this disclosure and knowledge of entities can readily determine the purpose and use of entities in the various embodiments and contexts disclosed herein.

[0270] The term party, as used herein, may be broadly understood to refer to members of an agreement, such as an individual, partnership, corporation, limited liability company, or other legal entity. For example, a party may be a primary lender, secondary lender, lending syndicate, corporate lender, government lender, bank lender, secured lender, bond issuer, bond purchaser, unsecured lender, guarantor, collateral provider, borrower, debtor, underwriter, examiner, appraiser, auditor, valuation expert, government official, accountant, or any other entity with rights or obligations to a contract, transaction, or loan. A party may be characterized in different terms, such as, but not limited to, a multi-party transaction, in which multiple parties are involved in a transaction. A party may represent itself or have a representative acting on its behalf. In certain embodiments, the term party may refer to a potential or prospective party—e.g., a willing lender or borrower interacting with the system, but who may not yet have committed to an actual agreement during their interaction with the system. Without limiting other aspects or descriptions of this disclosure, a party may also be used in combination with other related parties or terms of a contract or loan (e.g., representations, warranties, indemnities, agreements, outstanding debt, fixed interest rates, variable interest rates, etc.), payment amounts, payment schedules, balloon payment schedules, collateral designations, collateral fungibility designations, entity, guarantees, guarantors, collateral, personal guarantees, liens, terms, foreclosure conditions, default conditions, and default consequences), etc. A party may have a set of attributes, such as, but not limited to, identity, creditworthiness, activity, behavior, business practices, contract performance status, 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 whether a party has met a condition or covenant and may enable automated action or trigger other conditions or clauses if a party has not met such condition or covenant. Those skilled in the art with the benefit of this disclosure and knowledge of the parties can readily determine the purpose and use of parties in the various embodiments and contexts disclosed herein.

[0271] As used herein, the terms party attributes, entity attributes, or party / entity attributes may be broadly understood to describe the value, characteristics, or status of a party or entity. For example, party or entity attributes may include, 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 receivables, information regarding payables, information regarding collateral value, and other types of information. In certain embodiments, a smart contract may calculate a value, status, or condition associated with a party or entity attribute and may enable automated action or trigger other conditions or clauses if the party or entity does not meet such conditions or clauses. One of ordinary skill in the art with the benefit of this disclosure and knowledge of party or entity attributes can readily determine the purpose and use of these attributes in the various embodiments and contexts disclosed herein.

[0272] 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 may include an individual, partnership, corporation, limited liability company, or other legal entity. For example, without limitation, 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 with 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 limiting other aspects or explanations of this disclosure, the term "party" may also be used in combination with other related party or contract or loan terms, such as borrower, guarantor, representation, warranty, indemnity, agreement, outstanding debt, fixed interest rate, variable interest rate, payment amount, etc.; collateral designation, collateral fungibility designation, security, personal guarantee, lien, term, foreclosure condition, default condition, and default consequence, etc. In certain embodiments, the smart contract may calculate whether a lender has met a condition or covenant, and may enable automated actions, notifications, or alerts, or trigger other conditions or clauses, if the lender has not met such condition or covenant. One of ordinary skill in the art with the benefit of this disclosure and knowledge of lenders can readily determine the purpose and use of lenders in the various embodiments and contexts disclosed herein.

[0273] The term "crowdsourcing service" as used herein may broadly refer to a service offered or rendered in connection with a crowdsourcing model or transaction, in which a large number 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 transmitted 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 the loan. The crowdsourcing request may be made public. In certain embodiments, without limitation, the crowdsourcing service may be implemented by a smart contract, where the smart contract processes responses to the crowdsourcing request and automatically assigns a reward to information that meets the set of parameters configured for the crowdsourcing request. Those skilled in the art with the benefit of this disclosure and knowledge of crowdsourcing services can readily determine the purpose and use of crowdsourcing services in the various embodiments and contexts disclosed herein.

[0274] The term publishing services, as used herein, may be understood to describe a set of services for publishing crowdsourcing requests. Publishing services may be provided by, but are not limited to, a platform or system. In certain embodiments, but are not limited to, publishing services may be performed by a smart contract, whereby crowdsourcing requests are published or publishing is initiated by a smart contract. One of ordinary skill in the art with the benefit of this disclosure and knowledge of publishing services can readily determine the purpose and use of publishing services in the various embodiments and contexts disclosed herein.

[0275] The term interface, as used herein, is understood broadly to describe components, such as computer components, through which interaction or communication is achieved, and may be embodied in software, hardware, or a combination thereof. For example, an interface may serve many different purposes or be configured for different 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, or a cloud computing interface, or a combination thereof. An interface may function as a method of inputting, receiving, or displaying data within, but not limited to, lending, refinancing, collections, consolidation, factoring, brokerage, or foreclosure. An interface may also function as an interface for other interfaces. Without limiting other aspects or descriptions of the present disclosure, an interface may be used with or as part of an application, process, module, service, layer, device, component, machine, product, subsystem, interface, connection, or system. In certain embodiments, an interface may be embodied in software, hardware, or a combination thereof and may be stored on a medium or memory. Those skilled in the art, having the benefit of this disclosure and knowledge of interfaces, will be able to readily determine the purpose and use of interfaces in the various embodiments and contexts disclosed herein.

[0276] The term graphical user interface, as used herein, may be understood as a type of interface that allows a user to interact with a system, computer, or other interface, in which interaction or communication is achieved through 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 or be configured for different uses or contexts. Such interfaces may serve, without limitation, as a way to receive or display data using visual representations, stimuli, or interactive data. A graphical user interface may serve as an interface for another graphical user interface or other interface. Without limiting other aspects or descriptions of the present disclosure, a graphical user interface may be used in conjunction with an application, process, module, service, layer, device, component, machine, product, subsystem, interface, connection, or part of a system. In certain embodiments, a graphical user interface may be embodied in computer-readable instructions, hardware, or a combination thereof, and may be stored on a medium or memory. A graphical user interface may be configured for any input type, including a keyboard, mouse, touchscreen, 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 with the benefit of this disclosure and knowledge of graphical user interfaces can readily determine the purpose and use of the graphical user interface in the various embodiments and contexts disclosed herein.

[0277] The term "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 device, where interaction or communication is achieved through a graphical device or representation. A user interface may be a computer component and may be embodied in software, hardware, or a combination thereof. A user interface may be stored on a medium or in memory. A user interface may include drop-down menus, tables, forms, etc. with default, templated, recommended, or pre-set conditions. In certain embodiments, a user interface may include voice interaction. Without limiting other aspects or descriptions of the present disclosure, a user interface may be used in combination with an application, circuit, controller, process, module, service, layer, device, component, machine, product, subsystem, interface, connection, or part of a system. A user interface may serve many different purposes or be configured for different applications or contexts. For example, a lender-side user interface may include functionality for displaying multiple customer profiles but may be limited in the ability to make certain changes. A borrower-side user interface may include functionality for viewing user account details and making changes. A third-party neutral side interface (e.g., a third party that has no interest in the underlying transaction, such as a regulator, auditor, etc.) may have the ability to allow company oversight and viewing of 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; a third-party neutral side interface (e.g., a third party that has no interest in the underlying transaction, such as an auditor) may have the ability to manipulate the data, and may have scheduled access depending on the purpose for the third party's access, and the third-party neutral side interface (e.g., an auditor, etc.) does not have the ability to manipulate the data.Third-party stakeholder interfaces (e.g., collectors, debtor advocates, investigators, partial owners, and other third parties that may have an interest in the underlying transaction) may include functionality that allows for the display of certain user data with limitations on making changes. Many more features of these user interfaces may be utilized to implement embodiments of the systems and / or procedures described throughout this disclosure. Accordingly, the benefits of the present disclosure may be applied in a wide variety of processes and systems, and any such process or system may be considered a service herein. Those skilled in the art with the benefit of the disclosure and knowledge of user interfaces can readily determine the purpose and use of the user interface in the various embodiments and contexts disclosed herein. For those skilled in the art, specific considerations 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 characteristics to borrowers, lenders, and third parties, etc.

[0278] The terms "interface" and "dashboard" used herein may also be broadly understood to describe components through which interaction or communication is achieved, such as computer components that may be embodied in software, hardware, or a combination thereof. The interfaces and dashboards may acquire, receive, present, or otherwise manage items, services, offerings, or other aspects of a transaction or financing. For example, the interfaces and dashboards may serve many different purposes or be configured for different 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, or a cloud computing interface, or a combination thereof. The interfaces or dashboards may serve as a way to receive or display data in, but not limited to, the context of lending, refinancing, collections, consolidation, factoring, brokerage, or foreclosure. The interfaces or dashboards may also serve as an interface or dashboard for another interface or dashboard. Without limiting other aspects or descriptions of the present disclosure, an interface may be used in conjunction with an application, circuit, controller, process, module, service, layer, device, component, machine, product, subsystem, interface, connection, or part of a system. 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 in memory.Those skilled in the art, with the benefit of this disclosure and commonly 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.

[0279] The term "domain," as used herein, may be broadly understood to describe the scope or context of a transaction and / or communication related to a transaction. For example, domains 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 limiting other aspects or descriptions of the present disclosure, one or more domains may be utilized in connection with any application, circuit, controller, process, module, service, layer, device, component, machine, product, subsystem, interface, connection, or part of a system. In particular embodiments, a domain may be embodied in computer-readable instructions, hardware, or a combination thereof, and may also be stored on a medium or in memory. Those skilled in the art with the benefit of this disclosure and knowledge of domains can readily determine the purpose and use of domains in the various embodiments and contexts disclosed herein.

[0280] As used herein, the term request (and variations thereof) may be broadly understood to describe an action or instance of initiating or requesting that something (e.g., information, a response, an object, etc.) be provided. Particular types of requests may also serve many different purposes or be configured for different applications or contexts, such as, but not limited to, a formal legal request (e.g., a subpoena), a refinancing request (e.g., a loan), or a crowdsourcing request. Systems may be utilized not only to execute requests, but also to fulfill requests. When discussing legal actions, loan refinancing, or crowdsourcing services, various forms of requests may be included, but are not limited to these. One skilled in the art with the benefit of this disclosure and knowledge of the contemplated systems can readily determine the value of a request implemented in an embodiment. While specific examples of requests are described herein for illustrative purposes, any embodiment benefiting from this disclosure, and any considerations understood by one skilled in the art with the benefit of this disclosure, are specifically contemplated within the scope of this disclosure.

[0281] The term reward (and variations thereof) as used herein may be broadly understood to describe an object or consideration received or provided in response to an action or stimulus. Rewards can be, without limitation, monetary or non-monetary. Specific types of rewards can also serve many different purposes or be configured for different uses or contexts, such as, without limitation, reward events, reward claims, monetary rewards, rewards captured as datasets, reward points, and other forms of rewards. Rewards may be triggered, assigned, generated for innovation, offered for submission of evidence, requested, offered, selected, managed, configured, assigned, communicated, identified, as well as other actions, without limitation. Systems may be utilized to perform the aforementioned actions. Discussion of specific actions or incentives for specific actions may include, without limitation, various forms of rewards. In certain embodiments herein, rewards may be utilized as a specific incentive (e.g., rewarding a specific person who responds to a crowdsourcing request) or a general incentive (e.g., rewarding a successful crowdsourcing request response in addition to or in lieu of a reward for a specific person who responds). One of ordinary skill in the art with the benefit of the disclosure herein and knowledge of rewards can readily determine the value of the reward implemented in an embodiment. While specific examples of rewards 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.

[0282] The term robotic process automation system, as used herein, may be broadly understood to describe a system that can perform tasks or provide the needs of the disclosed system. For example, a robotic process automation system may be configured for, but is not limited to, negotiating a set of terms for a loan, negotiating a loan refinancing, collecting a loan, consolidating a set of loans, managing factored loans, brokering mortgage loans, training for foreclosure negotiations, configuring a crowdsourcing request based on a set of attributes for a loan, and setting rewards. It may also include determining a set of domains to which requests will be published, setting the content of the request, setting data collection and monitoring actions based on a set of loan attributes, determining a set of domains to which Internet of Things data collection and monitoring services will apply, 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 is an activity that includes marketing activities, identifying a set of prospective borrowers, identifying properties, identifying collateral, borrower qualifications, title searches, title confirmations, property appraisals, property inspections, property valuations, income verifications, borrower demographic analysis, identifying capital providers, determining available interest rates, determining available payment terms, analyzing existing mortgages, comparative analysis of existing and new mortgage terms, completing application workflows, populating application fields, preparing mortgage agreements, completing schedules to mortgage agreements, negotiating mortgage terms with capital providers, negotiating mortgage terms with borrowers, transferring title, placing liens, and completing mortgage agreements.An exemplary, non-limiting robotic process automation system may include one or more user interfaces, interfaces with system-wide circuits and / or controllers to provide, request, and / or share data, and one or more artificial intelligence circuits configured to iteratively improve one or more operations of the robotic process automation system. Those skilled in the art, with the benefit of the disclosure herein and generally available knowledge regarding 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, but any embodiment benefiting from the disclosure herein and any considerations that will be understood are included.

[0283] The term loan-related action (and other related terms, such as loan-related event and loan-related activity) is used herein and may be broadly understood to describe one or more actions, events, or activities related to a transaction that includes a loan within the transaction. Actions, events, or activities may occur in many different lending contexts, including, without limitation, financing, refinancing, consolidation, factoring, brokerage, foreclosure, administration, negotiation, collection, procurement, enforcement, and data processing (e.g., data collection), or any combination thereof. A loan-related action may be used in its noun form (e.g., a notice of default was communicated to a borrower in a formal notice, which may 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 providing a specific notice to a borrower about a delinquent payment, may be considered a loan-related action. Similarly, a series of actions related to a default from start to finish may also be considered a single loan-related action. Appraisal, inspection, funding, and recordkeeping may also be considered loan-related actions that have occurred, as may, but are not limited to, all loan-related events. Similarly, the activities that complete these actions may also be considered loan-related activities (e.g., without limitation, appraisals, inspections, funding, records, etc.). In particular embodiments, a smart contract or robotic process automation system may process appropriate tasks to perform and complete loan-related actions, events, or activities on behalf of one or more of the parties. In some cases, a smart contract or robotic process automation system may not complete a loan-related action, and depending on such outcome, this may enable automated actions or trigger other conditions or clauses.Those skilled in the art with the benefit of this disclosure and knowledge of 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.

[0284] The terms loan-related actions, events, and activities described herein may also be utilized more specifically to describe the context of a loan call. A loan call is an action that allows a lender to request repayment of a loan, typically triggered by some other condition or term, such as a late payment. For example, a loan may be called if a borrower misses three consecutive payments, causing serious delinquency in the loan payment schedule and putting the loan into default. In such a scenario, the lender may initiate a loan-related action for a loan call to protect its rights. In such a scenario, perhaps the borrower pays an amount to cure the delinquency and penalties, which may 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, which may include, but are 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 knowledge of loan-related actions for loan calling, 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.

[0285] As described herein, the terms loan-related actions, events, and activities may be used to more specifically describe the context of loan payments. Typically, in transactions involving loans, including but not limited to, loans, the loans are repaid based on a payment schedule. Various actions may be taken 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, loan-related actions for the loan payment may occur. Such a payment may consist of several actions that may occur related to the loan payment, including, but not limited to, a payment tendered 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 required 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 loan payment, 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 to the borrower regarding the next payment, or other actions related to the loan payment. 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 events or other various embodiments and contexts disclosed herein.

[0286] As described herein, the terms loan-related acts, events, and activities may be used more specifically to describe the context of a payment schedule or alternative payment schedule. Typically, but not exclusively, in transactions involving loans, loans are repaid based on a payment schedule, which may change over time. Alternatively, alternative payment schedules may be developed and agreed upon. Various actions may be taken by a lender or borrower in connection with a payment schedule or alternative payment schedule, such as the amount of the payment, the due date of the payment, the nature of any penalties or fees associated with late payments, or other terms. For example, if a borrower makes an early payment on a loan, a loan-related action may occur with respect to the loan payment schedule and alternative payment schedule. In this case, the payment would likely be applied as principal, and regular payments would still be due. Without limitation, loan-related actions for payment schedules and alternative payment schedules may consist of several actions that may occur with respect to the payment of a loan, such as a payment submitted 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, the calculation of any fees attached or due, and the next payment required 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, calculating the final payment amount and date, providing notice of the next payment due to borrowers, determining a payment schedule or alternative payment schedule, communicating the payment scheduler or alternative payment schedule, or other actions related to paying off a loan. Those skilled in the art having the benefit of the disclosure herein and knowledge of 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 or other various embodiments and contexts disclosed herein.

[0287] As used herein, the term regulatory notice requirement (and its derivatives) may be broadly understood to describe 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 triggered 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 the interest rate on the 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 mandate specific communication obligations. In certain embodiments, a policy directive may be treated as a regulatory notice requirement—for example, when a lender has 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 can take various forms, but may be specifically specified as a particular form of notice, such as certified mail, facsimile, email transmission, or other physical or electronic form, the content of the notice, and / or timing requirements related to the notice. The requirement aspect relates to the need for a party to complete its obligations to comply with a law, regulation, code, policy, standard practice, or the terms of a contract or loan. In certain embodiments, a smart contract can handle or trigger regulatory notification requirements and provide appropriate notifications to the borrower. This may be based on at least one location of the lender, the borrower, the funds provided via the loan, the repayment of the loan, and the collateral for the loan, or other location specified by the terms of the loan, transaction, or agreement. 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 the lender provides a non-compliance notice to the 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 effected by smart contract circuitry and / or robotic process automation systems—may be implemented.One of ordinary skill in the art with the benefit of this disclosure and commonly available knowledge of the contemplated systems can readily determine the purpose and application of regulatory notification requirements in the various embodiments and contexts disclosed herein.

[0288] The term regulatory notice requirement may also be used herein to describe an obligation or condition to communicate a notice or message to another party or entity based on general or specific policy rather than on the law, regulation, or code of a specific jurisdiction or location (as in regulatory notice requirements, which may be jurisdiction-specific). Regulatory notice requirements may be prudent or suggested, rather than obligatory or required, under one or more conditions that are triggered or generally required. For example, a lender may have a policy-based regulatory notice requirement to notify borrowers about a new information site, future changes to loan interest rates, or provide other notices related to the transaction or loan that are advisory or helpful, but not mandatory (although mandatory notices may also fall under policy grounds). Thus, in policy-based uses of the term regulatory notice requirement, smart contract circuitry can process or trigger regulatory notice requirements and provide appropriate notices to borrowers that may not necessarily be required by law, regulation, or code. The basis for the notice or communication may be prudence, courtesy, custom, or obligation.

[0289] The term regulatory notice may also be used herein to express an obligation or condition to specifically communicate a notice or message to another party or entity, such as a lender or borrower. Regulatory notices may be specifically directed to any party or entity, or to a group of parties or entities. For example, it may be desirable or required for a particular notice or communication to be provided to a debtor, such as when the debtor defaults on a loan by failing to make a scheduled repayment. As such, such regulatory notices directed to particular users, such as lenders or borrowers, may be the result of jurisdiction-specific or policy-based regulatory notice requirements, or may not otherwise be so. Accordingly, 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, which is not necessarily required by law, rule, or code, but may otherwise be provided out of prudence, courtesy, or custom. Failure of a party or entity to meet such regulatory notice requirements for a particular party may create a situation in which certain rights are waived by one or more parties or entities, or which enables automatic action or triggers other conditions or clauses. Those skilled in the art, with the benefit of this disclosure and commonly available knowledge of the contemplated system, will be able to readily determine the purpose and application of the regulatory notice requirements based on the various embodiments and contexts disclosed herein.

[0290] As used herein, the term regulatory foreclosure requirement (and its derivatives) may be broadly understood to refer to obligations or conditions for triggering, processing, or completing a loan default, auction, or repossession of collateral, or other related foreclosure action. Regulatory foreclosure requirements may be triggered or required under one or more generally required conditions. For example, a lender may have a regulatory foreclosure requirement to provide a borrower with notice of a loan default prior to foreclosure or to provide other notices related to a loan default. The regulatory aspect of the term may result from jurisdiction-specific laws, regulations, or codes that require specific communication obligations. The foreclosure aspect generally relates to the specific remedies of foreclosure or repossession of collateral and loan default, which can 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 due to compliance with or performance of a law, regulation, code, or contract or loan term. In certain embodiments, smart contract circuitry may process or trigger regulatory foreclosure requirements and handle appropriate tasks related to such foreclosure actions. 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. If a party or entity fails to meet such regulatory foreclosure requirements, certain rights may be waived by the party or entity (e.g., a lender), or failure to meet such regulatory notice requirements may enable automated action or trigger other conditions or clauses. Those skilled in the art, with the benefit of this disclosure and generally available knowledge of the contemplated systems, will be able to readily determine the purpose and application of regulatory foreclosure requirements in the various embodiments and contexts disclosed herein.

[0291] The term regulatory foreclosure requirement is also used herein to describe an obligation or order for triggering, processing, or completing a loan, foreclosure, repossession of collateral, or other related foreclosure action. It is based on general or specific policy, rather than on the laws, regulations, or codes of a particular jurisdiction or location (as regulatory foreclosure requirements are jurisdiction-specific). Regulatory foreclosure requirements may be prudent or suggestive, or generally required, under one or more conditions that trigger them. For example, a lender may have a policy-based regulatory foreclosure requirement to notify a borrower 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 term regulatory foreclosure requirement, a smart contract may process or trigger the regulatory foreclosure requirement and provide appropriate notices to the borrower that are not necessarily required by law, regulation, or code. The basis for the notice or communication may be prudence, courtesy, custom, industry practice, or obligation.

[0292] The term regulatory foreclosure requirements may also be used herein to describe obligations or conditions that must be fulfilled with respect to specific users, such as lenders or borrowers. Regulatory notices may be specifically directed to any party or entity, or to a group of parties or entities. For example, it may be desirable or required to provide a specific notice or communication to a debtor, such as when the debtor defaults on a loan by failing to make scheduled payments. As such, such regulatory foreclosure requirements may be directed to specific users, such as lenders or borrowers, and may be the result of jurisdiction-specific or policy-based or other regulatory foreclosure requirements. For example, foreclosure requirements may relate to specific entities involved in a transaction (e.g., a current borrower receives unique treatment because he or she has been a customer for 30 years) or classes of entities (e.g., a "preferred" borrower or a "first-time default" borrower). Thus, in some situations, smart contract circuitry may process or trigger obligations or actions that must be taken pursuant to a foreclosure or action directed by a particular party, such as a lender or borrower, which may or may not necessarily be required by law, regulation, or code, but may otherwise be provided out of prudence, courtesy, or custom. In certain embodiments, an obligation or condition to be performed with respect to a particular user may form part of the terms and conditions or otherwise be known to the particular user to whom it applies (e.g., as follows: an insurance company or bank may advertise certain practices with respect to a particular class of customers, such as first-time default customers, first-time accident customers, etc.), while in certain embodiments, an obligation or condition to be performed with respect to a particular user may be unknown to the particular user to whom it applies (e.g., a bank may have a policy regarding the class of users to which a particular user belongs, but the particular user is unaware of that classification).

[0293] The terms value, valuation, valuation model (and similar terms) used herein should be understood broadly to describe approaches to evaluating and determining the estimated value of collateral. Without limiting other aspects or descriptions of this disclosure, a valuation model may be used in connection with collateral (e.g., collateralized property), artificial intelligence services (e.g., to improve valuation models), data collection and monitoring services (e.g., to set valuations), valuation services (e.g., the process of informing, using, and / or improving valuation models), and / or results related to transactions in collateral (e.g., as a basis for improving valuation models). A "jurisdictional valuation model" may also refer to a valuation model used in a particular geographic / jurisdictional area or region, where the jurisdiction may be specific to the lender, borrower, grant of funds, loan disbursement, or loan collateral jurisdiction, or a combination thereof. In certain embodiments, the jurisdiction-specific valuation model considers jurisdictional effects on collateral valuation, including at least the rights and obligations of borrowers and lenders in the relevant jurisdiction, the jurisdiction's effect on the ability to transfer, import, export, substitute, and / or liquidate collateral, the jurisdiction's effect on the timing between default and foreclosure or collection of collateral, and / or the jurisdiction's effect on the volatility and / or sensitivity of collateral value determinations. In certain embodiments, the geographically located valuation model considers geographic location effects on collateral valuation. This may include a similar list of considerations of relative jurisdictional effects (although jurisdictional location(s) may differ from geographic location(s)), but may also include additional effects such as weather-related effects, the collateral's distance from monitoring, maintenance, or seizure services, and / or proximity to risk phenomena (e.g., faults, industrial areas, nuclear power plants, etc.). The valuation model may utilize valuations of offsetting collateral (e.g., generic values ​​such as similar items of collateral, market values ​​of similar or convertible collateral, and / or values ​​of items correlated to 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 to improve the valuation model, for example, by utilizing historical information between multiple transactions involving similar or offsetting collateral and / or utilizing outcome information from the same or other transactions (e.g., in response to successful or unsuccessful completion of loan transactions and / or collateral seizure or liquidation events indicating actual collateral valuation determinations) to iteratively improve the valuation model. In certain embodiments, the artificial intelligence circuitry is trained through interaction with collateral valuation datasets, e.g., previously determined valuations, and / or trainers (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 a transaction (e.g., a loan, a set of loans, and / or a subset of a set of loans). One of ordinary skill in the art with the benefit of this disclosure and commonly available knowledge of the contemplated systems will readily be able to determine which aspects of the present disclosure will benefit a particular application for the valuation model and how to select or combine valuation models to implement embodiments of the valuation model. Particular considerations for one of ordinary skill in the art in selecting an appropriate valuation model or for embodiments of the present disclosure include, but are not limited to, the following: legal considerations of the valuation model taking into account the jurisdiction of the collateral, available data for a given collateral, the expected transaction / loan type, the specific collateral type, loan to value ratio, collateral to loan ratio, total transaction / loan amount, borrower creditworthiness, loan type and / or related industry accounting practices, uncertainties related to any of the foregoing, and / or sensitivity considerations related to any of the foregoing. While specific examples of valuation models and considerations 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 having the benefit of the disclosure herein, are specifically contemplated within the scope of the present disclosure.

[0294] As used herein, the term market value data or market information (and other forms or variations) may be broadly understood to refer to data or information regarding the valuation of real estate, assets, collateral, or other valuables that may be used as the subject of a loan, security, or transaction. Market value data or market information changes from time to time and may be estimated, calculated, or determined objectively or subjectively from a variety of sources. Market value data or market information may relate directly to the collateral or to offset collateral. Market value data or market information may include financial data, market ratings, product ratings, customer data, market research to understand customer needs or preferences, competitive information regarding competitors, suppliers, etc., actual sales, transactions, customer acquisition costs, customer lifetime value, brand awareness, churn rates, etc. The term may occur, without limitation, in many different contexts of contracting or financing, including lending, refinancing, consolidation, factoring, brokerage, foreclosure, data processing (e.g., data collection), or 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, market value data or market information may be utilized by a lender to determine whether a property or asset serves as collateral for a secured loan, or alternatively, in foreclosure decisions when a loan is in default, although the use of the term is not limited to these situations. Market value data or market information may also be used to determine loan-to-value figures or calculations. In certain embodiments, a collection service, smart contract circuitry, and / or robotic process automation system may estimate or calculate market value data or market information from one or more sources of data or information. In some cases, market data values ​​or market information may enable automated actions or trigger other conditions or clauses depending on the data / information contained therein.Those skilled in the art, having the benefit of this disclosure and commonly available knowledge of the contemplated systems and relevant market information available, will be able to readily determine the purpose and application of this term in the various forms, embodiments and contexts disclosed herein.

[0295] As used herein, the terms similar collateral, similar to collateral, offsetting collateral, and other forms or variations thereof may be broadly understood 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 may refer to property, assets, collateral, or other items of value that may be aggregated, substituted, or otherwise referenced in connection with other collateral, whether the similarity comes in the form of common attributes such as type of collateral, category of collateral, age of collateral, condition of the collateral, history of the collateral, ownership of the collateral, caretaker of the collateral, collateral security, status of the owner of the collateral, liens on the collateral, storage condition of the collateral, geographic location of the collateral, and jurisdictional location of the collateral. In certain embodiments, offsetting collateral refers to items that have a value correlation with the item of collateral—for example, the offsetting collateral may exhibit similar price fluctuations, volatility, storage requirements, etc., relative to the item of collateral. In certain embodiments, similar collateral may be aggregated to form a larger security interest or collateral for an additional loan or distribution or transaction. In certain embodiments, offsetting collateral may be utilized to inform the valuation of collateral. In certain embodiments, smart contract circuitry or robotic process automation systems may estimate or calculate values, data, or information related to similar collateral or perform functions related to aggregating similar collateral. One of ordinary skill in the art with the benefit of this disclosure and commonly available knowledge of the contemplated systems can readily determine the purpose and use of similar collateral, offsetting collateral, or related terms related to collateral in the various forms, embodiments, and contexts disclosed herein.

[0296] As used herein, the term restructuring (and other forms of restructuring) may be broadly understood to refer to the modification of terms, conditions, collateral, or other considerations affecting a loan or transaction. Restructuring may be, but is not limited to, a successful outcome in which the parties adopt modified terms, or an unsuccessful outcome in which no modification or restructuring takes place. Restructuring can occur in many aspects of a contract or loan, including, but not limited to, applications, lending, refinancing, collections, consolidations, factoring, brokerage, foreclosures, and combinations thereof. Debt may also be restructured, which may indicate that debt owed to one party is changed with respect to timing, amount, collateral, or other terms. For example, a borrower may restructure a loan to address a change in financial circumstances, or a lender may offer a debt restructuring to a borrower for its own needs or prudence. In certain embodiments, the smart contract circuitry or robotic process automation system can automatically or manually restructure debt or create options for restructuring debt based on monitored conditions, manage the process of negotiating or effecting debt restructuring, or take other actions related to restructuring or modifying the terms of a loan or transaction. 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 the purpose and application of this term in the various embodiments and contexts disclosed herein, whether in the context of debt or otherwise.

[0297] As used herein, the terms social network data collection, social network monitoring service, and social network data collection and monitoring service (and various forms or derivatives thereof) may be broadly understood to refer to services related to obtaining, organizing, observing, or otherwise acting on data or information obtained from one or more social networks. Social network data collection and monitoring services may be part of a related service system or a standalone service set. Social network data collection and monitoring services may be provided by a platform or system, including but not limited to lending, refinancing, negotiation, collection, consolidation, factoring, brokerage, foreclosure, and combinations thereof. Social network data collection and monitoring requests, along with configuration parameters, may be requested by other services, initiated automatically, or triggered to occur based on conditions or circumstances that occur. Interfaces may be provided for configuring, initiating, viewing, or otherwise interacting with the social network data collection and monitoring service. As used herein, a social network refers to any popular 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 authorization). In certain embodiments, social network data includes information that is appropriately accessible to an embodiment system, but may include subscription or other access to information that is not publicly available but may be 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, academic-oriented networks, etc.In certain embodiments, the social network may be a crowdsourcing platform, such as a platform configured to accept queries or requests directed to users (and / or subsets of users, potentially meeting specified criteria), where users may acknowledge that certain communications will be shared and accessible to the requester, at least a portion of the platform's users, and / or will be publicly available. In certain embodiments, without limitation, the social network data collection and monitoring service may be implemented by smart contract circuitry or a robotic process automation system. One of ordinary skill in the art with the benefit of this disclosure and commonly available knowledge of the contemplated systems can readily determine the purpose and uses of the social network data collection and monitoring service in the various embodiments and contexts disclosed herein.

[0298] The term crowdsourced and social network information, as used herein, may also be broadly understood to describe information obtained or provided in connection with a crowdsourcing model or transaction, or information 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, or the crowdsourced and social network information may be managed by smart contract circuitry that processes the information to meet a set of configured parameters. One of ordinary skill in the art with the benefit of this disclosure and commonly available knowledge of the contemplated systems can readily determine the purpose and use of this term in the various embodiments and contexts disclosed herein.

[0299] As used herein, the term negotiation (and other forms, such as negotiation or negotiation) may be broadly understood to refer to discussions or communications between parties or entities to bring about or obtain a compromise, outcome, or agreement. Negotiations may result in, but are not limited to, a successful outcome in which terms are agreed upon between the parties, or an unsuccessful outcome in which the parties do not agree to certain terms, or a 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 many contract or financing contexts, including, but not limited to, loans, refinancing, collections, consolidation, factoring, brokerage, foreclosure, and combinations thereof. For example, a borrower may negotiate interest rates and loan terms with a lender. In another example, a borrower that has defaulted on its loan may negotiate with a lender an alternative solution to avoid foreclosure. In certain embodiments, smart contract circuitry or a robotic process automation system may process appropriate tasks to negotiate and complete or attempt to complete the negotiation of terms on behalf of one or more of the parties. In some cases, negotiation by a smart contract or robotic process automation system may not be completed or may be unsuccessful. Successful negotiation may enable automated actions implemented by the smart contract circuitry or robotic process automation system, or may trigger other conditions or clauses. Those skilled in the art, with the benefit of this disclosure 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.

[0300] The term negotiation in its various forms may be used herein, more specifically, in the verb form (e.g., negotiate) or the noun form (e.g., bargain), or other forms that describe the context of mutual discussion leading to an outcome. For example, a robotic process automation system may negotiate terms on behalf of the parties, which would be its use as a verb phrase. In another example, the robotic process automation system may be negotiating terms for a loan modification, or negotiating a merger offer, or other terms. As a noun phrase, the negotiation (e.g., an event) may be performed by the robotic process automation system. Thus, in some situations, a smart contract circuit or robotic process automation system may negotiate terms (e.g., as a verb phrase), or a description of doing so may be considered a negotiation (e.g., as a noun phrase). Those skilled in the art, having the benefit of this disclosure and knowledge of negotiation and negotiation, or other forms of the word negotiate, can readily determine the purpose and use of this term in the various embodiments and contexts disclosed herein.

[0301] Additionally, the term negotiation in its various forms may be utilized to express, among other things, an outcome, such as the completion of negotiations leading to a mutual compromise or result. For example, a loan may be considered negotiated, such as by a robotic process automation system, as a successful outcome in which negotiations have reached completion and resulted in an agreement between the parties. Thus, in some situations, a smart contract circuit or robotic process automation system may be negotiating a set of terms or conditions to complete a negotiated loan. One skilled in the art with the benefit of the disclosure herein and commonly available knowledge of the contemplated systems can readily determine the purpose and use of this term in relation to a mutually agreed upon outcome through the completion of negotiations in the various embodiments and contexts disclosed herein.

[0302] The term negotiation in its various forms may also be utilized to characterize events, such as negotiation events, specifically events that involve arriving at a set of mutually agreeable terms between parties. Events that require mutual agreement or compromise between parties may be considered, without limitation, negotiation events. For example, during loan procurement, the process of arriving at a set of mutually agreeable terms between parties may be considered a negotiation event. Thus, in some circumstances, smart contract circuitry or robotic process automation systems may accommodate the communication, actions, or behavior of parties for a negotiation event.

[0303] As used herein, the term collection (and other forms such as collection or acquisition) may be broadly understood to describe the acquisition of tangible (e.g., physical items), intangible (e.g., data, licenses, or rights), or monetary (e.g., payment) items, or other obligations or assets, from a source. The term may generally relate to the entire prospect of acquiring such items, from early-stage related work to later-stage related work or full completion of the acquisition of the items. Collection may result in, 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., a late or otherwise defective bid for the item). Collection may occur in many different contexts of contracting or financing, such as, but not limited to, lending, refinancing, consolidation, factoring, brokerage, foreclosure, data processing (e.g., data collection), or a combination thereof. Collect may be used in its noun form (e.g., collecting data referring to or characterizing an event or collecting past due amounts), may refer to an assortment of items as a noun (e.g., collecting collateral for a loan referring to multiple items in a transaction), or may be used in its verb form (e.g., collecting payments from a borrower). For example, a lender may collect past due amounts from a borrower through online payment or may successfully collect past due amounts obtained through a customer service call. In certain embodiments, smart contract circuitry or a 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., past due amounts). In some cases, negotiations by a 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 with the benefit of this disclosure and commonly available knowledge of the contemplated systems can readily determine the purpose and use of collect in the various forms, embodiments, and contexts disclosed herein.

[0304] Additionally, the term collection in its various forms may be utilized herein in its noun form to more specifically describe the context of an event or thing, such as a collection event or a collection payment. For example, a collection event may refer to, but is not limited to, a communication to a party or other activity related to the acquisition of an item in that activity. A collection payment may relate to, for example, a payment made by a borrower obtained through a collection process or through a lender's collection department. While 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 a delinquent payment. 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 be considered, without limitation, a collection event.

[0305] Additionally, the term collection in its various forms may be utilized herein as an adjective or other form to more specifically describe a litigation-related context, such as the outcome of a collection action (e.g., a lawsuit regarding loan delinquency or nonpayment). For example, the outcome of a collection action may be related to past due payments owed by a borrower or other party, and collection efforts related to those past due payments may be litigated by the party. Thus, in some situations, a smart contract circuit or robotic process automation system may receive, determine, or otherwise manage the outcome of a collection action.

[0306] Also, more specifically, various forms of the term collection may be utilized herein as adjectives or other forms to describe contexts relating to the act of obtaining, such as a collection action (e.g., an action to induce the tendering or acquisition of delinquent or defaulted payments on a loan or other debt). The terms collection rate, collection financial yield, and / or collection financial yield may be used. The outcome of such collection actions may or may not have a financial yield. For example,...

Claims

1. 1. A method for configuring a role-based digital twin, comprising: generating, by a processing system, a digital twin of the marketplace, the digital twin being a digital representation of a structure of the marketplace, the structure having a set of marketplace entities including assets and roles; determining, by a processing system, a set of relationships between different roles for a set of entities in the marketplace; determining, by a processing system, a configuration of roles from a set of roles based on the determined set of relationships; providing a set of configurations for a set of roles using the determined set of relationships in the marketplace structure; The step of linking a set of identities to a role; determining, by the processing system, a role-based marketplace orchestration digital twin presentation layer configuration corresponding to each respective role based on a set of role configurations linked to identities of the set of identities, the presentation layer configuration defining a set of states to be depicted in the role-based marketplace orchestration digital twin associated with the role; determining, by a processing system, a set of data sources providing data corresponding to the set of states, each data source providing one or more respective types of data; and Configuring one or more data structures to store data received from a set of data sources, the one or more data structures configured to provide data used to populate one or more of a set of states of a role-based market orchestration digital twin.

2. The method of claim 1 , further comprising linking the set of identities to a set of roles, each identity corresponding to a respective role from the set of roles.

3. 2. The method of claim 1, wherein the role-based marketplace orchestration digital twin integrates with a marketplace orchestration platform operating on the role-based marketplace orchestration digital twin such that changes in the marketplace orchestration platform are automatically reflected in the role-based marketplace orchestration digital twin.

4. The method of claim 1 , wherein the set of settings for the set of roles comprises role-based permission settings.

5. The method of claim 1 , wherein the set of settings for the set of roles comprises role-based preference settings.

6. The method of claim 5 , wherein the role-based preference settings are configured based on a set of role-specific templates.

7. The method of claim 6 , wherein the set of role-specific templates includes at least one of a trader template, a marketplace host template, a broker template, a buyer template, or a seller template.

8. The method of claim 1 , wherein the set of role set configurations comprises a set of role-based taxonomy configurations.

9. 10. The method of claim 8, wherein the role-based taxonomy configuration identifies taxonomies used to characterize data presented in the role-based marketplace orchestration digital twin, such that data is presented in a taxonomy linked to a corresponding role in the role-based marketplace orchestration digital twin.

10. 10. The method of claim 9, wherein the set of role-based taxonomies includes at least one of a trader template, a marketplace host template, a broker template, a buyer template, or a seller template.

11. The method of claim 1 , wherein the at least one role is a trader role, a marketplace host role, a broker role, a buyer role, or a seller role.

12. 2. The method of claim 1, wherein the at least one role comprises a market maker role, a market analyst role, an exchange administrator role, a broker-dealer role, a trading role, a settlement role, a contract counterparty role, an exchange rate setting role, a marketplace orchestration role, a marketplace configuration role, or a contract configuration role.

13. 2. The method of claim 1, wherein the role is a chief marketing officer role, a product development role, a supply chain manager role, a customer role, a supplier role, a vendor role, a demand management role, a marketing manager role, a sales manager role, a service manager role, a demand forecasting role, a retail manager role, a warehouse manager role, a sales representative role, or a distribution center manager role.

14. 1. A method for training an intelligent agent, comprising: receiving digital twin data from a set of data sources, the digital twin data comprising: physical entity data received from a set of data resources monitoring a set of monitored physical entities associated with the marketplace, the physical entity data being transported by a set of network entities; and a marketplace data stream generated by a set of marketplace assets, the set of marketplace assets including at least one of a physical entity associated with the marketplace or a digital entity associated with the marketplace; structuring the digital twin data into a set of digital twin data structures configured to provide a plurality of distinct role-based digital twins; receiving a request for a role-based digital twin from a client application, the role-based digital twin being configured with respect to a role within the marketplace; determining a subset of the structured digital twin data that corresponds to a set of states depicted in a role-based digital twin; providing a subset of the structured digital twin data to the client application; receiving intelligent agent training data sets from the client applications, each intelligent agent training data set indicative of respective actions taken by a user using the client application and one or more features corresponding to each action; and training an intelligent agent on behalf of a user based on an intelligent agent training dataset, wherein the intelligent agent is configured to determine an action to be performed on behalf of the user, and the determined action to be performed is either recommended to the user or automatically performed on behalf of the user.

15. The method of claim 14 , wherein the role is a trader role, a marketplace host role, a broker role, a buyer role, or a seller role.

16. 15. The method of claim 14, wherein the role is a market maker role, an exchange administrator role, a broker-dealer role, a trading role, a settlement role, a contract counterparty role, an exchange rate setting role, a marketplace orchestration role, a marketplace configuration role, or a contract configuration role.

17. 15. The method of claim 14, wherein the role is a chief marketing officer role, a product development role, a supply chain manager role, a customer role, a supplier role, a vendor role, a demand management role, a marketing manager role, a sales manager role, a service manager role, a demand forecasting role, a retail manager role, a warehouse manager role, a sales representative role, or a distribution center manager role.

18. The method of claim 14 , wherein the intelligent agent training data set comprises interaction training data indicative of a set of interactions by the user with the set of experts while performing the role.

19. 20. The method of claim 18, wherein the set of interactions used to train the intelligent agent includes interactions of a user with a physical entity.

20. 20. The method of claim 18, wherein the set of interactions used to train the intelligent agent includes user interactions with the role-based digital twin.

21. 20. The method of claim 18, wherein the set of interactions used to train the intelligent agent includes user interactions with the sensor data as depicted in the role-based digital twin.

22. 20. The method of claim 18, wherein the set of interactions used to train the intelligent agent includes at least one interaction of a set of experts with a marketplace data stream generated by a physical entity.

23. 20. The method of claim 18, wherein the set of interactions used to train the intelligent agent includes interactions of at least a subset of the set of experts with one or more computational entities.

24. 20. The method of claim 18, wherein the set of interactions used to train the intelligent agent includes interactions of a user with one or more network entities.

25. 20. The method of claim 18, wherein the intelligent agent is trained to determine actions including at least one of selecting an asset, pricing the asset, configuring a marketplace, listing an asset on a marketplace, uploading information related to an asset listed on the marketplace, identifying a counterparty, selecting a counterparty, identifying an opportunity, selecting an opportunity, conducting negotiations, identifying a need for a new marketplace, digitally inspecting the asset, physically inspecting the asset, configuring a digital twin, placing an order request, generating a smart contract, physically delivering the asset, physically retrieving the asset, selecting a trading strategy, brokering a trade, valuing the asset, or matching an order.

26. 20. The method of claim 18, wherein the intelligent agent is trained with a training set of outcomes resulting from actions taken by a user.

27. 27. The method of claim 26, wherein the training set of outcomes includes data regarding at least one of financial outcomes, operational outcomes, failure outcomes, success outcomes, performance index outcomes, output outcomes, consumption outcomes, energy utilization outcomes, resource utilization outcomes, cost outcomes, profit outcomes, revenue outcomes, sales outcomes, or production outcomes.

28. Intelligent agents can: determine the system architecture, report on status, report on events, report on context, report on conditions, determine the model, configure the model, input the model, design the system, design the process, design the equipment, engineer the system, engineer the equipment, engineer the process, engineer the product, maintain the system, maintain the equipment, maintain the process, maintain the network, maintain the computational resources, maintain the equipment, maintain the hardware, repair the system, repair the device, repair the process, repair the network, repair the computational resources, repair the equipment, repair the hardware, assemble the system, assemble the device, assemble the process, assemble the network, assemble the computational resources, assemble the equipment, assemble the hardware, set the price, physically secure the system, physically secure the device, physically secure the process, network Physically secure, physically secure the system, physically secure the device, physically secure the process, physically secure the network, physically secure the computing resources, physically secure the equipment, physically secure the hardware, cybersecure the system, cybersecure the device, cybersecure the process, cybersecure the network, cybersecure the computing resources, cybersecure the equipment, software, detect threats, detect failures, tune the system, tune the device, tune the process, tune the network, tune the computing resources, tune the equipment, tune the software, optimize the system, optimize the system, optimize the device, optimize the process, optimize the network, optimize the computing resources, optimize the equipment, optimize the hardware, monitor the system, monitor the device, monitor the process, monitor the network, monitor the computing resources, monitor the equipment, monitor the hardware, configure the system, configure the device, configure the process, configure the network, configure the computing resources, configure the equipment, or configure the hardware,19. The method of claim 18, wherein the user is trained to perform actions including at least one of:

29. 15. The method of claim 14, wherein the intelligent agent is at least one of trained and configured via feedback from at least one expert in a defined role on a set of outputs of the intelligent agent.

30. 30. The method of claim 29, wherein the set of outputs of the intelligent agent to which the at least one expert provides feedback includes at least one of a recommendation, a classification, a prediction, a control instruction, an input selection, a protocol selection, a communication, an alert, a target selection for communication, a data storage selection, a computation selection, a configuration, an event detection, or a prediction.

31. 31. The method of claim 30, wherein feedback of at least one expert is solicited to train the intelligent agent to replicate the expertise of the role expert.

32. 32. The method of claim 31, wherein feedback of the at least one expert is used to modify the set of inputs to the intelligent agent.

33. 33. The method of claim 32, wherein feedback of the at least one expert is used to identify and characterize at least one error by the intelligent agent.

34. 34. The method of claim 33, wherein a report of the set of errors is provided to a user of the intelligent agent to enable reconfiguration of the intelligent agent based on feedback from the expert.

35. 35. The method of claim 34, wherein reconfiguring the intelligent agent includes at least one of removing an input that is the source of at least one error, reconfiguring a set of nodes of the intelligent agent, reconfiguring a set of weights of the intelligent agent, reconfiguring a set of outputs of the intelligent agent, reconfiguring a processing flow within the intelligent agent, or augmenting a set of inputs to the intelligent agent.

36. 15. The method of claim 14, wherein an intelligent agent is trained based on the training set of results to provide training and / or guidance to individuals fulfilling defined roles in the marketplace.

37. 37. The method of claim 36, wherein the training set of outcomes includes data regarding at least one of financial outcomes, operational outcomes, failure outcomes, success outcomes, performance index outcomes, output outcomes, consumption outcomes, energy utilization outcomes, resource utilization outcomes, cost outcomes, profit outcomes, revenue outcomes, sales outcomes, or production outcomes.

38. 20. The method of claim 18, further comprising analyzing the training data set of interactions to identify types of actions taken by users when analyzing the set of interactions.

39. 40. The method of claim 38, wherein the type of processing includes at least one of audio processing, analysis of audio information, tactile processing, textual information processing, motion processing, visual processing, spatio-temporal processing, mathematical processing, or analytical processing.

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