Systems, methods, and apparatus for consolidating a set of loans
AssigneeStrong Force TX Portfolio 2018, LLC
InventorCharles Howard Cella
Life of this patent
Estimating the term…
Abstract
Systems, methods and apparatus for a robotic process automation system for consolidating a set of loans are disclosed herein. An example system may include a set of data collection and monitoring services for collecting information about a set of loans and for collecting a training set of interactions between entities for a set of loan consolidation transactions; an artificial intelligence system that is trained on the training set of interactions to classify a set of loans as candidates for consolidation; and a robotic process automation system that is trained on a set of loan consolidation interactions to manage consolidation of at least a subset of the set of loans on behalf of a party to the consolidation.
Claims18
A method for validating conditions of collateral, the method comprising:
- providing a graphical user interface in communication with a set of processors, the graphical user interface being configured to enable a workflow by which a requesting human user configures a crowdsourcing request via the graphical user interface with a set of conditions, wherein the crowdsourcing request is configured to request information related to a condition, of the set of conditions, of one or more physical collateral items for a new loan from a set of potential information suppliers after detection of an event:
- receiving, by the set of processors, the set of conditions from the requesting human user;
- configuring, by the set of processors, a smart contract that manages the new loan that is secured by the one or more physical collateral items based on a set of loan parameters agreed to by a lender and a borrower that owns the one or more physical collateral items;
- configuring, by the set of processors, an intelligence system to:
- continuously monitor information streams received about the one or more physical collateral items, wherein the information streams comprise sensor data captured from sensors in a vicinity of the physical collateral items, wherein the intelligence system comprises a neural network classifier trained to detect the event based on the information streams;
- upon detection of the event, cause an indication that the event was detected to be sent to the smart contract:
- deploying, by the set of processors, the smart contract to a smart contract platform that executes the smart contract, and upon execution by the smart contract platform, the smart contract:
- after receiving the indication that the event was detected, publishing the crowdsourcing request to at least one of the potential information suppliers via a set of application programming interfaces (APIs) and a communication network;
- receiving and processing, by the set of processors, a set of responses to the crowdsourcing request, the set of responses being received by the smart contract via the communication network and the set of APIs from a set of devices associated with one or more information suppliers of the set of potential information suppliers, wherein the set of responses include a plurality of images;
- and
- in response to verifying a respective successful information supplier event corresponding to the crowdsourcing request, instructing, via the set of APIs, a distributed ledger network to transfer a reward to a respective account of a respective successful information supplier of the one or more information suppliers;
- evaluating, by the set of processors, the plurality of images together with additional data received from the information streams comprising sensor data captured from the sensors in the vicinity of the one or more physical collateral items, wherein the evaluating comprises:
- processing, by the set of processors, the plurality of images together with the additional data received from the information streams comprising sensor data captured from the sensors in the vicinity of the one or more physical collateral items to generate inputs for a machine vision model of the intelligence system;
- and
- evaluating, by the machine vision model executed by the set of processors, the inputs to determine the condition of the one or more physical collateral items;
- generating, by the set of processors, an estimated value for the one or more physical collateral items based on the condition of the one or more physical collateral items;
- and
- reconfiguring, by the set of processors, the set of loan parameters within the smart contract based on the estimated value.
A non-transitory computer-readable storage medium storing instructions that, when executed by a set of processors, cause the set of processors to perform steps comprising:
- providing a graphical user interface in communication with the set of processors, the graphical user interface being configured to enable a workflow by which a requesting human user configures a crowdsourcing request via the graphical user interface with a set of conditions, wherein the crowdsourcing request is configured to request information related to a condition, of the set of conditions, of one or more collateral items for a new loan from a set of potential information suppliers after detection of an event;
- receiving the set of conditions from the requesting human user;
- configuring a smart contract that manages the new loan that is secured by the one or more collateral items based on a set of loan parameters agreed to by a lender and a borrower that owns the one or more collateral items;
- configuring an intelligence system to:
- continuously monitor information streams received about the one or more collateral items, wherein the information streams comprise sensor data captured from sensors in a vicinity of the one or more collateral items, wherein the intelligence system comprises a neural network classifier trained to detect the event based on the information streams;
- upon detection of the event, cause an indication that the event was detected to be sent to the smart contract:
- deploying the smart contract to a smart contract platform that executes the smart contract, and upon execution by the smart contract platform, the smart contract:
- after receiving the indication that the event was detected, publishing the crowdsourcing request to at least one of the potential information suppliers via a set of application programming interfaces (APIs) and a communication network;
- receiving and processing, by the set of processors, a set of responses to the crowdsourcing request, the set of responses being received by the smart contract via the communication network and the set of APIs from a set of devices associated with one or more information suppliers of the set of potential information suppliers, wherein the set of responses include a plurality of images;
- and
- in response to verifying a respective successful information supplier event corresponding to the crowdsourcing request, instructing, via the set of APIs, a distributed ledger network to transfer a reward to a respective account of a respective successful information supplier of the one or more information suppliers;
- evaluating the plurality of images together with additional data received from the information streams comprising sensor data captured from the sensors in the vicinity of the one or more collateral items, wherein the evaluating comprises:
- processing the plurality of images together with the additional data received from the information streams comprising sensor data captured from sensors in the vicinity of the one or more collateral items to generate inputs for a machine vision model of the intelligence system;
- evaluating, by the machine vision model, the inputs to determine the condition of the one or more collateral items;
- generating an estimated value for the one or more collateral items based on the condition of the one or more collateral items;
- and
- reconfiguring the set of loan parameters within the smart contract based on the estimated value.
Dependencies are inferred from the claim text.