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US 11,776,069 B2Granted
Systems and methods using IoT input to validate a loan guarantee
AssigneeStrong Force TX Portfolio 2018, LLC
InventorCharles Howard Cella
Life of this patent
Estimating the term…
Abstract
Systems and methods using IOT input to validate a loan guarantee are disclosed. An example system may include an Internet of Things (IoT) data input circuit to interpret a loan guarantee parameter; an IoT data collection circuit to collect data using at least one algorithm that is configured to monitor IoT information collected from and about an entity involved in a loan in response to the loan guarantee parameter; and a guarantee validation circuit to validate a guarantee for the loan in response to the monitored IoT information.
Claims22
A system, comprising:
- a set of processors providing a loan guarantee validation service, wherein each processor within the set of processors forms part of at least one of a server, a cloud server, a computer network, a mobile computing platform, or a stationary computing platform, and wherein the set of processors includes:
- an Internet of Things (IoT) data input circuit structured to:
- provide a graphical user interface configured to enable a workflow by which a human user enters a loan guarantee parameter to establish an IoT data collection request, and
- interpret the loan guarantee parameter;
- an IoT data collection circuit structured to collect data using at least one algorithm that is configured to monitor IoT information collected from and about an entity involved in a loan in response to the loan guarantee parameter;
- a guarantee validation circuit structured to validate a guarantee for the loan in response to the monitored IoT information;
- and
- a robotic process automation circuit structured to:
- maintain a training data set comprising human user interactions with the graphical user interface provided by the IoT data input circuit, the training data set including the loan guarantee parameter provided by the human user,
- iteratively train a model based on the training data set,
- configure a new loan guarantee parameter corresponding to a new loan based on the model and at least one attribute of the new loan, and
- update the training data set based on an outcome of the new loan, and
- wherein the robotic process automation circuit is structured to iteratively train the model further based on the training data set as updated based on the outcome of the new loan.
10 more elements
A method, comprising:
- providing, via a set of processors that provides a loan guarantee validation service, a graphical user interface that enables a workflow by which a human user enters a loan guarantee parameter to establish an Internet of Things (IoT) data collection request, wherein each processor within the set of processors forms part of at least one of a server, a cloud server, a computer network, a mobile computing platform, or a stationary computing platform;
- interpreting, via the set of processors, the loan guarantee parameter provided by the human user;
- collecting, via the set of processors, data using a plurality of algorithms that is configured to monitor IoT information collected from and about an entity involved in a loan in response to the loan guarantee parameter;
- validating, via the set of processors, a guarantee for the loan in response to the monitored IoT information;
- maintaining, via the set of processors, a training data set comprising at least one of outcomes from or human user interactions with the plurality of algorithms via the graphical user interface in connection with a plurality of loans that includes the loan, wherein the training data set includes the loan guarantee parameter provided by the human user;
- and
- iteratively performing:
- training, via the set of processors, a model for an automated robotic process on the training data set;
- configuring, via the set of processors, an IoT data collection and monitoring action corresponding to a new loan based on the model and at least one attribute of the new loan;
- and
- updating, via the set of processors, the training data set based on an outcome of the new loan.
8 more elements
Dependencies are inferred from the claim text.