Abstract: Apparatus and methods for determining transaction transmission fidelity are provided. A sender may receive a transaction log including multiple transactions in two or more rows and two or more columns. The transaction log may be encrypted. Each of the transactions may be tagged. Each row and column of the transaction log may be hashed. The encrypted transaction log and the hash values may be transmitted to a recipient. The recipient may decrypt the transaction log and hash each row and column of the decrypted transaction log. The hash values may be compared and if there is a difference, a report or alert may be generated.

Abstract: A computer system for optimizing an application for monitoring operation of a network is provided. The application may utilize Artificial Intelligence (AI). The computer system may be configured to detect a network transaction volume level that exceeds a first threshold level. In response to a detection of the network transaction volume level that exceeds a first threshold level, the system may utilize the AI to determine whether to implement one or more over-threshold-level mitigation techniques. When the AI instructs the processor to implement the one or more over-threshold-level mitigation techniques, the system may query the AI for an instruction directing an implementation of the over-threshold-level mitigation techniques.

Abstract: Systems and methods for lossless restoration of a digital system are provided. A method may include creating a digital twin of the digital system. Creating the digital twin may include constructing a digital model that replicates hardware and software components and performance metrics of the digital system. The components and the performance metrics may be detected via a plurality of edge devices. The digital model may be configured to be run on a processor to simulate performance of the digital system. The method may include receiving an indication that the digital system is disconnected from a central server, syncing the digital twin with the digital system while the digital system is disconnected from the central server, and, in response to an indication that the digital system has reconnected with the central server, syncing the central server with the digital twin.

Abstract: Systems and methods for maximizing resource utilization in a digital communication system are provided. A method may include receiving a direction for a first one of a plurality of edge devices to execute a task, wherein the edge devices communicate with each other and with a central server via a communication network. The central server may be operated by an entity that is independent of the communication network. The plurality of edge devices may each include an authenticated software application that is provided by the entity. The method may also include calculating, via the ML engine for each of the plurality of edge devices, a predicted resource availability score, and distributing, via the central server, the task among the plurality of edge devices based on the predicted resource availability scores.

Abstract: Methods and systems for using block chain technology to verify transaction data are described herein. A computing platform may receive data about events related to transactions, personal or corporate information, supply chains, and other relevant information about a person or corporate entity. The event information may be received, aggregated, and processed to determine metadata about the person or corporate entity. The metadata may indicate, for example, a trustworthiness of the person or corporate entity for various purposes. Such event information and/or metadata may be stored as transactions in a block chain that may be accessible by counterparties to a potential transaction involving the person or corporate entity. The automated event processing computing platform may further use automated techniques to implement smart transactions between the person/entity and counterparty based on the trust metadata.

Abstract: Methods and systems for using block chain technology to verify transaction data are described herein. A computing platform may receive data about events related to transactions, personal or corporate information, supply chains, and other relevant information about a person or corporate entity. The event information may be received, aggregated, and processed to determine metadata about the person or corporate entity. The metadata may indicate, for example, a trustworthiness of the person or corporate entity for various purposes. Such event information and/or metadata may be stored as transactions in a block chain that may be accessible by counterparties to a potential transaction involving the person or corporate entity. The automated event processing computing platform may further use automated techniques to implement smart transactions between the person/entity and counterparty based on the trust metadata.

Abstract: Systems for using cognitive automation techniques to detect unauthorized events are provided. In some examples, a request for a product or service (e.g., event processing) may be received. The request may be received electronically, via a telephone communication, in person, or the like. The request may be analyzed (e.g., using a cognitive automation model) to determine whether it is potentially unauthorized. If so, one or more requests for additional information may be generated or identified. For instance, requests for authentication information, responses to questions or a series of questions, or the like, may be generated. In some examples, the additional information requested may be identified using the cognitive automation model. Responses to the request for additional information may be analyzed (e.g., using the cognitive automation model) to determine whether the request for the product or service is unauthorized. If so, processing the request may be prevented.

Abstract: This application describes apparatus and methods for using edge-computing to control resource distribution among access channels, such as a retail banking center. Edge-nodes may be configured to move a product display in response to detected or expected customer traffic flow in or near a retail location. Edge-nodes may be configured to redirect resources provided by a cloud computing environment to or away from the retail location. Based on customer traffic flow, edge-nodes may direct customers/resources to a retail location and ensure the retail location provides a predetermined quality of service.

Abstract: Methods and systems for using block chain technology to verify transaction data are described herein. A computing platform may receive data about events related to transactions, personal or corporate information, supply chains, and other relevant information about a person or corporate entity. The event information may be received, aggregated, and processed to determine metadata about the person or corporate entity. The metadata may indicate, for example, a trustworthiness of the person or corporate entity for various purposes. Such event information and/or metadata may be stored as transactions in a block chain that may be accessible by counterparties to a potential transaction involving the person or corporate entity. The automated event processing computing platform may further use automated techniques to implement smart transactions between the person/entity and counterparty based on the trust metadata.

Abstract: Aspects of the disclosure relate to cognitive automation-based engine processing on audio files and streams received from meetings and/or telephone calls. A noise mask can be applied to enhance the audio. Real-time speech analytics separate speech for different speakers into time-stamped streams, which are transcribed and merged into a combined output. The output is parsed by analyzing the combined output for correct syntax, normalized by breaking the parsed data into record groups for efficient processing, validated to ensure that the data satisfies defined formats and input criteria, and enriched to correct for any errors and to augment the audio information. Notifications based on the enriched data may be provided to call or meeting participants.

Abstract: Methods and systems for using block chain technology to verify transaction data are described herein. A computing platform may receive data about events related to transactions, personal or corporate information, supply chains, and other relevant information about a person or corporate entity. The event information may be received, aggregated, and processed to determine metadata about the person or corporate entity. The metadata may indicate, for example, a trustworthiness of the person or corporate entity for various purposes. Such event information and/or metadata may be stored as transactions in a block chain that may be accessible by counterparties to a potential transaction involving the person or corporate entity. The automated event processing computing platform may further use automated techniques to implement smart transactions between the person/entity and counterparty based on the trust metadata.

Abstract: A system for capturing communication variables associated with a communication between two or more parties and implementing a quantum optimizer to analyze the communication variables to determine the actual context of a communication held by one or more parties to the communication. Once the actual context is determined, a further determination is made as to whether the actual context poses or potentially poses a security threat to one or more parties to the communication or a third-party and, if so, notifies the party of the security threat. In this regard, parties to a communication that are unaware of the actual context of the communication held by another party are made aware of that actual context poses a security threat and, in some embodiments, notifies the parties while the communication is still occurring.

Abstract: Methods and systems for using block chain technology to verify transaction data are described herein. A computing platform may receive data about events related to transactions, personal or corporate information, supply chains, and other relevant information about a person or corporate entity. The event information may be received, aggregated, and processed to determine metadata about the person or corporate entity. The metadata may indicate, for example, a trustworthiness of the person or corporate entity for various purposes. Such event information and/or metadata may be stored as transactions in a block chain that may be accessible by counterparties to a potential transaction involving the person or corporate entity. The automated event processing computing platform may further use automated techniques to implement smart transactions between the person/entity and counterparty based on the trust metadata.

Abstract: Methods and systems for using block chain technology to verify transaction data are described herein. A computing platform may receive data about events related to transactions, personal or corporate information, supply chains, and other relevant information about a person or corporate entity. The event information may be received, aggregated, and processed to determine metadata about the person or corporate entity. The metadata may indicate, for example, a trustworthiness of the person or corporate entity for various purposes. Such event information and/or metadata may be stored as transactions in a block chain that may be accessible by counterparties to a potential transaction involving the person or corporate entity. The automated event processing computing platform may further use automated techniques to implement smart transactions between the person/entity and counterparty based on the trust metadata.

Abstract: Methods and systems for using block chain technology to verify transaction data are described herein. A computing platform may receive data about events related to transactions, personal or corporate information, supply chains, and other relevant information about a person or corporate entity. The event information may be received, aggregated, and processed to determine metadata about the person or corporate entity. The metadata may indicate, for example, a trustworthiness of the person or corporate entity for various purposes. Such event information and/or metadata may be stored as transactions in a block chain that may be accessible by counterparties to a potential transaction involving the person or corporate entity. The automated event processing computing platform may further use automated techniques to implement smart transactions between the person/entity and counterparty based on the trust metadata.

Abstract: Methods and systems for using block chain technology to verify transaction data are described herein. A computing platform may receive data about events related to transactions, personal or corporate information, supply chains, and other relevant information about a person or corporate entity. The event information may be received, aggregated, and processed to determine metadata about the person or corporate entity. The metadata may indicate, for example, a trustworthiness of the person or corporate entity for various purposes. Such event information and/or metadata may be stored as transactions in a block chain that may be accessible by counterparties to a potential transaction involving the person or corporate entity. The automated event processing computing platform may further use automated techniques to implement smart transactions between the person/entity and counterparty based on the trust metadata.

Abstract: Methods and systems for using block chain technology to verify transaction data are described herein. A computing platform may receive data about events related to transactions, personal or corporate information, supply chains, and other relevant information about a person or corporate entity. The event information may be received, aggregated, and processed to determine metadata about the person or corporate entity. The metadata may indicate, for example, a trustworthiness of the person or corporate entity for various purposes. Such event information and/or metadata may be stored as transactions in a block chain that may be accessible by counterparties to a potential transaction involving the person or corporate entity. The automated event processing computing platform may further use automated techniques to implement smart transactions between the person/entity and counterparty based on the trust metadata.

Abstract: A system for exchanging authentication data between edge-nodes is provided. The system may include an edge-node network. The network may include a plurality of edge-nodes. Each edge-node may include a pairing module. Each pairing module may receive an instruction to pair with another edge-node. Each pairing module pair with another edge-node. The pairing module may continually transmit verification communications to other edge-nodes. The pairing module may continually discover responsive communications from other edge-nodes. The pairing module may continually receive responsive verification communications from other edge-nodes. Each edge-node may include an executable module. The executable module may determine occurrence of an event. Upon determination of the occurrence of an event, the executable module may analyze a stored event protocol. The protocol including an algorithm for implementing executables in response to an event.

Abstract: Aspects of the invention relate to components for constructing a payment instrument that includes enhanced electronic features. Apparatus may include an all-inclusive smart card that securely stores sensitive data. Such sensitive data may include credit card, driver's license or passport information. The smart card may generate disposable card numbers for online or offline onetime transactions.

Abstract: Systems for using cognitive automation techniques to detect unauthorized events are provided. In some examples, a request for a product or service (e.g., event processing) may be received. The request may be received electronically, via a telephone communication, in person, or the like. The request may be analyzed (e.g., using a cognitive automation model) to determine whether it is potentially unauthorized. If so, one or more requests for additional information may be generated or identified. For instance, requests for authentication information, responses to questions or a series of questions, or the like, may be generated. In some examples, the additional information requested may be identified using the cognitive automation model. Responses to the request for additional information may be analyzed (e.g., using the cognitive automation model) to determine whether the request for the product or service is unauthorized. If so, processing the request may be prevented.