2117results about "Payment circuits" patented technology

This invention provides a comprehensive maritime shipbroking platform uniting digital twin modeling, AI-driven cargo allocation, blockchain-based contract management, predictive maintenance (AR / VR), route optimization, real-time tracking, and single-window compliance. The digital twin engine continuously simulates vessel performance, enabling data-driven decisions on stowage, scheduling, and maintenance. A cargo-freight matching module optimally allocates shipments, factoring in market rates, vessel metrics, and port congestion. Blockchain-secured smart contracts automate negotiations, ensuring transparency and tamper-proof enforcement. A predictive maintenance system applies advanced analytics to diagnose technical issues early, while the route optimization engine finds cost-effective, emission-compliant routes. Real-time tracking gives stakeholders constant visibility, and the single-window interface integrates Electronic Bill of Lading processes, satisfying IMO and IG P&I standards. Additionally, a dynamic vessel ranking system incorporates SIRE, RightShip, PSC, and user feedback for safer, more efficient chartering decisions. The invention addresses day-to-day operational challenges in maritime logistics, elevating efficiency and compliance.

An artificial intelligence driven system of systems may include a layered architecture for providing transaction support to various types of enterprises. A governance layer implements automated governance and policy enforcement through specialized governance modules utilizing generative AI technology. An enterprise layer supports enterprise functions by integrating management and control platforms with digital infrastructure. An offering layer creates and manages system offerings via content generation, personalization, and smart product modules. A transactions layer enables automated transaction orchestration through API integration, execution, and fulfillment modules. An operations layer manages AI systems through generation, training, verification and orchestration modules. A network layer provides adaptive networking capabilities through routing, protocol selection and communication modules. A data layer processes fused data from multiple sources using machine learning and AI systems. A resource layer manages computing, storage, and other resources through specialized resource modules.

Presented herein are systems and methods for the employment of machine learning models for image processing as may be performed by computing devices associated with an end user. A method may include obtaining video data comprising a plurality of frames including a document of a document type. The method may include executing an object recognition engine of a machine-learning architecture using image data of the plurality of frames, the object recognition engine trained to detect edges of documents. The method may include identifying, based on the edge detection, a plurality of boundaries for the document. The method may include validating, based on the plurality of boundaries, the document as the document type. The method may include transmitting via one or more networks, to a computer remote from the computing device, responsive to the validation of the type of document, the image data for the plurality of frames depicting the document.

In embodiments, systems and methods for configuring and deploying artificial intelligence driven transacting agents that are permitted to autonomously execute transactions on behalf of the individual or organization and configuring the transacting agent based on the agent configuration instructions and a set of predefined system prompts. The method further includes granting the transacting agent access to a digital wallet associated with the individual or organization and deploying the transacting agent to a public network, such that the transacting agent executes transactions on behalf of the individual or organization via one or more digital marketplaces using the digital wallet to which the transacting agent was granted access. In some embodiments, the transacting agent is granted access to the digital wallet using a consent token. In some embodiments, the method also includes hyper-personalizing and / or fine-tuning the agent.

The present invention relates to the technical field of dynamic carbon sink accounting, and specifically relates to a dynamic carbon sink accounting system based on multi-modal AI remote sensing monitoring and blockchain-based evidence storage. The system collects optical remote sensing, radar, photosynthetically active radiation and meteorological data, performs unified spatiotemporal calibration on the data, and then fuses the calibrated data by means of a cross-modal attention mechanism, so as to generate multi-modal feature vectors, and inputs same into a TCN model for carbon stock and trend prediction. A prediction result and metadata are uploaded to a blockchain by means of smart contracts, so as to generate a carbon sink NFT including a geographic fence and a confidence level, thereby realizing trusted evidence storage. A residual mapping function is established in view of on-chain historical data, so as to dynamically optimize the model, and improve the accounting accuracy. The system improves the fusion capability and prediction accuracy, and enhances the credibility and transparency of carbon asset management and transactions.

The invention relates to the technical field of carbon sink dynamic accounting, in particular to a carbon sink dynamic accounting system based on multi-mode AI remote sensing monitoring and block chain evidence storage. The system collects optical remote sensing, radar, photosynthetically active radiation and meteorological data, after unified space-time calibration, multi-modal feature vectors are generated through cross-modal attention mechanism fusion, and the multi-modal feature vectors are input into a TCN model to predict carbon reserves and trends. And a prediction result and metadata are chained through an intelligent contract to generate a carbon sink NFT containing a geographic fence and confidence, so that credible evidence storage is realized. And a residual mapping function is established in combination with historical data on the chain, the model is dynamically optimized, and the accounting precision is improved. The system improves the fusion capability and prediction accuracy, and enhances the credibility and transparency of carbon asset management and transaction.

Systems and methods for staking instrument cryptocurrency rewards and validator management are disclosed. The systems and methods include generating validator pods associated with cryptocurrency staking validation and generating validator keys configured to be utilized by the validator pods for validating proof of stake operations. A subsets of the validator keys may be assigned to the validator pods and a request to perform the proof of stake operations may be received. A validator pod may be provisioned for validating proof of stake operations, and the validator node may be utilized to validate proof of stake operations based on the selected validator node being a compliant validator node.

Methods and systems for remote check deposit are disclosed. A check for deposit is processed without the need for a server to receive any image of the check initially. Instead, optical character recognition (OCR) data is received at the server from a mobile device. Verification processing for the check is then performed using the OCR data. If the verification process is successful, a confirmation notification is sent to the mobile device. Subsequently, after sending the confirmation notification, a check image is received, from which the OCR data was determined. The check is, in turn, processed for deposit using the received check image.

The invention discloses a cross-border e-commerce block chain payment credit chain system and a method thereof, and realizes data sharing, information real-time synchronization and credit information dynamic transmission of each participant in a transaction by constructing an alliance block chain network. The system comprises a credit management module, a risk control module, an intelligent contract payment module, a digital currency exchange module and a security collaboration module, and multi-dimensional credit assessment, dynamic risk prediction and automatic payment are realized by using cross-domain technologies such as federated learning, trusted execution environment and homomorphic encryption. Through fund freezing, real-time digital currency exchange, payment triggered by performance conditions and other mechanisms, the cross-border payment clearing period is remarkably shortened, the transaction cost is reduced, the payment safety and supervision transparency can be improved, and the problems that traditional cross-border payment is low in efficiency, high in cost, difficult in risk control and the like are effectively solved.

Systems and techniques may be used to perform multi-capture for remote deposit via scanner. For example, a technique may include scanning a first side and a second side of a plurality of checks, and comparing geometrical features of the first side of each check of the plurality of checks to geometrical features of the second side of each check of the plurality of checks. Based on the comparison, the technique may include selecting an image from a first set of respective individual images that corresponds to an image from a second set of respective individual images to form a pair of images, the pair of images representing a single check of the plurality of checks, and outputting the pair of images.

Techniques are described, as implemented by computing devices, to control access to digital content through use of nonfungible tokens (NFTs). This is performed by leveraging a blockchain such that digital content associated with an item is made available to supplement use of the item (e.g., to supplement use of a physical item, digital content, and so forth) or make other functionality available based on a user's possession of the item.

Embodiments are directed toward a blockchain system including a global state and an assemblage of blocks, each block representing a collection of state transformation records, each state transformation record describing a state transformation performed on the global state, where preceding blocks referenced by any given block contain state transformation records describing state transformations performed on the global state prior to the evaluation of the given block, and where at least one state transformation record is a zero-knowledge transformation record encoding a zero-knowledge state transformation description, which zero-knowledge transformation record comprises at least the following elements: paths identifying the locations of the elements of a discrete data subset, a revised data subset, and a transition proof implemented as a non-interactive zero-knowledge proof, which transition proof proves that the transition from the discrete data subset to the revised data subset follows the established rules of the blockchain system.

A computer implemented method, system, and non-transitory computer-readable device for conducting a document type assessment. In some embodiments, a machine learning (ML) model (e.g., an image classification ML model) may be trained to determine a document type and / or document type acceptability from an image. In some embodiments, the ML model may determine the document type and / or document type acceptability in real-time, within a current customer transaction period before the customer submits a deposit or access request or immediately after in response to the customer submitting the deposit or access request. In some embodiments, document types determined by the ML model may be used to track user patterns and perform a comparison of past user patterns with a current deposit or access attempt, improving security. In some embodiments, document types determined by the ML model may be used to customize validation protocols for images.

Aspects of the present disclosure describe a system comprising a processor and memory storing instructions, which when executed by the processor, enable the system to detect a payment-related event using vehicle sensors, such as a camera or GPS unit. The detection can involve a machine learning model trained to recognize objects associated with the payment-related event while minimizing false positives. Upon detecting the event, the system can handle the electronic payment by utilizing an in-vehicle digital wallet to execute the payment and recording the transaction on a blockchain-based ledger.

Methods and systems for remote check deposit are disclosed. A check for deposit is processed without the need for a server to receive any image of the check initially. Instead, optical character recognition (OCR) data is received at the server from a mobile device. Verification processing for the check is then performed using the OCR data. If the verification process is successful, a confirmation notification is sent to the mobile device. Subsequently, after sending the confirmation notification, a check image is received, from which the OCR data was determined. The check is, in turn, processed for deposit using the received check image.

Disclosed herein are system, apparatus, device, method and / or computer program product embodiments for identifying, in a remote deposit system, a level of correspondence of a financial instrument with past deposit activity. The level of correspondence may be used to determine a funds availability schedule and / or identify counterfeit financial instruments. In some embodiments, the level of correspondence may be determined by comparing a date associated with the financial instrument to a date parameter, an amount of the financial instrument to an amount parameter, and / or one or more financial instrument characteristics with one or more payer-specific financial instrument characteristics.

The present disclosure involves systems, software, and computer implemented methods for transaction auditing. One example method includes receiving text submitted with a request. Token values are automatically extracted for selected token types from the text using a machine learning model. Tokens are identified in the text, and for each token, features and a token type of the token are determined, along with a score that indicates a likelihood that the token has the token type. A token value is extracted for the token from the text. Extracted token values are compared to request data values. A request value for the selected token type is identified in the data values for each selected token type. The extracted token value for each selected token type is compared to the request value. An audit alert is generated in response to determining that an extracted token value does not match a corresponding request value.

Systems and methods are provided for training an artificial intelligence system and generating audible content for output. The method utilizing a system including at least an application plane layer, a control plane layer including a cognitive computing unit, the cognitive computing unit using at least machine learning for training of the cognitive computing unit, a training input to the system including an input for receiving content for training during the machine learning, and a data plane layer, the data plane layer including an input interface to receive and store data input content from one or more data sources other than the control plane layer, the data input content being subject to transformation into audible content for output. Data input content information is used in synthesizing audible output content at least in part by transforming the data input content into the audible output content.

Improve user convenience. 【Solution means】The setting acquisition unit (104) of the payment system (1) acquires settings regarding installment payment, recurring payment, or bonus payment of payment means available to the user. The processing execution unit (102) executes processing regarding installment payment, recurring payment, or bonus payment based on the settings. The setting release unit (105) releases the settings based on a predetermined release condition.

A computer implemented method, system and non-transitory computer-readable device for a remote deposit environment activating, on a client device, a financial application, wherein the financial application is configured to instantiate a customer interface (UI) on the client device. Upon receiving a customer request, based on interactions with the UI, the method implements an electronic deposit of a financial instrument by generating a live stream of image data of a field of view of at least one camera, wherein the live stream of image data includes imagery of at least a portion of the financial instrument, determining, based on the live stream of image data and a machine learning model (ML), an impermissibility score of the financial instrument and, based on exceeding a selectable threshold of the impermissibility score, modifying a status of the remote deposit to pause or terminate the remote deposit.

Disclosed herein are system, apparatus, device, method and / or computer program product embodiments for determining, in a remote deposit system, whether a deposit attempt is illegitimate (e.g. fraudulent). Whether the deposit attempt is illegitimate may be assessed based on one or more of the following processes: comparing location data to a location parameter determined from past deposits, comparing an image capture location with a deposit location, and analyzing image-of-image characteristics obtained through image processing to identify whether an image associated with the deposit attempt is an image of an image. In some embodiments, a remote deposit status related to acceptance of the deposit attempt may be provided in real-time

Systems and methods for fault tolerant digital payments are disclosed. The system comprises a computing system that can automatically determine if payments should be processed using a digital payment processing system, or using a blockchain. When the system detects that communication with the digital payment processing system has been interrupted, the system may facilitate transactions through the blockchain. In particular, the system can retrieve private keys for addresses on the blockchain and facilitate customer payments through the blockchain.

The Asynchronous Crypto Asset Transfer and Social Aggregating, Fractionally Efficient Transfer Guidance, Conditional Triggered Transaction, Datastructures, Apparatuses, Methods and Systems (“SOCOACT”) transforms transfer of assets (TOA) initiation request inputs via SOCOACT components into TOA confirmation outputs. A crypto asset transfer notification is sent to a first entity from a second entity. Account verification data generated by the second entity is determined. A set of account data stored by the first entity is retrieved and used to generate a hash. It is verified that the determined account verification data matches the generated hash. A requested asset is determined. An API call to generate a crypto token asset for the requested asset in a socially aggregated blockchain datastructure is made. An address of an aggregated crypto transaction trigger entry is determined. Oracle data that satisfies the crypto smart rule is provided.

A secure cryptocurrency transactional system for actuating transactions involving electronic gaming machines and cryptocurrency wallets.

Embodiments provide artificial intelligence methods and systems for evaluating vulnerability risks of issuer authorization system. Method performed by a server system includes accessing a set of payment transaction data including subset of fraudulent transaction data. Method includes generating via a machine learning model, set of synthetic transaction data based on the subset of fraudulent transaction data. Method includes accessing set of historical card velocity features and collating the set of synthetic transaction data and the set of historical card velocity features to generate set of enriched synthetic transaction data. Method includes extracting via a classifier, subset of feasible fraudulent transaction data from the set of enriched synthetic transaction data. Method includes generating simulated authorization model based on the set of payment transaction data. Method includes classifying via simulated authorization model, each enriched synthetic transaction from the subset of feasible fraudulent transaction data as one of fraudulent transaction and non-fraudulent transaction.

A computer implemented method, system, and non-transitory computer-readable device for a remote deposit environment. In some embodiments, a predictive machine learning (ML) model may be trained to determine a likelihood an image will be successfully processed via OCR. The predictive ML model may determine the likelihood prior to the image being uploaded to a remote server and / or processed via OCR, allowing the image to be rejected and replaced in real time. In some embodiments, the predictive ML model may be implemented on a mobile device. Optionally, the predictive ML model may be supported by a deep learning model operating to refine the predictive ML model.

A system and associated method and service for providing a platform that enables members to transfer, receive, or otherwise exchange cash in various international denominations and commodities, such as precious metals (e.g., gold, silver, etc.), in a mobile highly secured telecommunications environment. The system is capable of delivering cash instantly between two or more users by allowing the exchange of secure transactions between system and cash dispensing machines (ATMs). Users may pay, receive, exchange, deposit, transfer, pay bills, exchange currency, retrieve cash, deposit cash and create accounts based on the mobile phone number or a system generated code.

A computer implemented system and a method for providing user related data, such as reputational information, on users of a blockchain involved in transactions is detailed. The method includes an approach for evaluating fulfilment of transactions, particularly in the context of contracts, and then providing a record of that on the blockchain through reputational information. As a result, at a late time, this reputational information can be retrieved. Similar reputational information for other transactions can be retrieved and linked to the same user, for instance based on the use of a hash of the master public key for a user. Aggregate reputational information can be computed from the pieces of reputational information retrieved.