IP Library › Granted Patent US 11,727,505
Granted Patent B2
US 11,727,505 · App. 16/998,910 · Granted Aug 15, 2023

Systems, methods, and apparatus for consolidating a set of loans

Inventor: Charles Howard Cella (Pembroke, MA)
Assignee: Strong Force TX Portfolio 2018, LLC
G06Q50/01G06F9/466G06F9/543G06F16/2379G06F16/27G06F18/22G06F18/23G06F18/241G06N3/042G06N3/08G06N5/04G06N20/00G06Q10/0639G06Q10/10G06Q20/405G06Q30/018G06Q30/0201G06Q30/0206G06Q30/0208G06Q30/0215G06Q30/0278G06Q40/03G06Q40/08G06Q50/18G06Q50/188G06Q50/26G06V10/762G16Y10/50G16Y40/10H04L9/0637G06Q40/04G06Q2220/18
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 11,727,505
App. No.
16/998,910
Filed
Aug 20, 2020
Granted
Aug 15, 2023
Kind
B2
Art Unit
3694
USPC
705/80
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.

Claims (192)

1. A system for consolidating a set of loans, comprising:

at least one processor;

a set of data collection and monitoring services that executes on the at least one processor and collects:

information about a set of loans,

a condition of a collateral for the set of loans, and

a set of electronically recorded interactions and outcomes between entities for a set of loan consolidation transactions,

wherein the set of data collection and monitoring services monitors the condition of the collateral for the set of loans, and

wherein the at least one processor maintains a training data set comprising the set of electronically recorded interactions and outcomes between the entities for the set of loan consolidation transactions;

a blockchain service circuit structured to interface with a distributed ledger having a blockchain, wherein the blockchain service circuit communicates with the set of data collection and monitoring services to generate data on the blockchain corresponding to the information about the set of loans, the condition of the collateral for the set of loans as monitored by the set of data collection and monitoring services, and the set of electronically recorded interactions and the outcomes between the entities for the set of loan consolidation transactions;

an artificial intelligence circuit that executes on the at least one processor and is trained, by the at least one processor, on the set of electronically recorded interactions and classifies the set of loans as candidates for consolidation based on the set of electronically recorded interactions; and

a robotic process automation (RPA) circuit that is trained, by the at least one processor, on the training data set, and wherein the RPA circuit communicates with the artificial intelligence circuit to:

receive the condition of the collateral as monitored by the set of data collection and monitoring services from the blockchain data as accessed from the blockchain via a first application programming interface (API); and

manage consolidation of at least a subset of the set of the classified loans on behalf of a party to one or more of the candidates for the consolidation,

wherein the RPA circuit manages the consolidation based on an expected outcome of a consolidation activity that is predicted based on the condition of the collateral as monitored by the set of data collection and monitoring services, and

the RPA circuit further manages the consolidation by:

automatically setting conditional steps and automatically executing the conditional steps based on the condition of the collateral as monitored by the set of data collection and monitoring services,

wherein the conditional steps include:

automatically facilitating, via a second API, a negotiation of a term of the set of loans; and

updating the training data set based on an outcome of the negotiation,

wherein the at least one processor further trains the RPA circuit on the updated training data set,

wherein the at least one processor determines at least one of the outcome or a negotiating event of the negotiation associated with the consolidation, and records, in the distributed ledger, the at least one of the outcome or the negotiating event, and

wherein upon completion of the negotiation, the at least one processor automatically configures a smart contract for a consolidated loan based on the outcome of the negotiation.

2. The system of claim 1 , wherein the set of data collection and monitoring services receives and analyzes data from at least one of:

a set of Internet of Things systems that monitor the entities,

a set of cameras that monitor the entities,

a set of software services that pull information related to the entities from publicly available information sites,

a set of mobile devices that report on information related to the entities,

a set of wearable devices worn by human entities, a set of user interfaces by which entities provide information about the entities, or

a set of crowdsourcing services configured to solicit and report information related to the entities.

3. The system of claim 1 , wherein the set of loans that are classified as candidates for consolidation are determined based on a model that processes attributes of entities involved in the set of loans, wherein the attributes include at least one of:

identity of a party,

interest rate,

payment balance,

payment terms,

payment schedule,

type of loan,

type of collateral,

financial condition of party,

payment status,

condition of collateral, or

value of collateral.

4. The system of claim 1 , wherein managing consolidation includes managing at least one of:

preparation of a consolidation offer,

preparation of a consolidation plan,

preparation of content communicating a consolidation offer,

scheduling a consolidation offer,

communicating a consolidation offer,

preparing a consolidation agreement,

executing a consolidation agreement,

modifying collateral for a set of loans,

handling an application workflow for consolidation,

managing an inspection,

managing an assessment, or

setting a payment schedule.

5. The system of claim 1 , wherein the entities are a set of parties to a loan transaction.

6. The system of claim 5 , wherein the set of parties includes at least one of:

a primary lender,

a secondary lender,

a lending syndicate,

a corporate lender,

a government lender,

a bank lender,

a secured lender,

bond issuer,

a bond purchaser,

an unsecured lender,

a guarantor,

a provider of security,

a borrower,

a debtor,

an underwriter,

an inspector,

an assessor,

an auditor,

a valuation professional,

a government official, or

an accountant.

7. The system of claim 1 , wherein the artificial intelligence circuit includes at least one of:

a machine learning system,

a model-based system,

a rule-based system,

a deep learning system,

a hybrid system,

a neural network,

a convolutional neural network,

a feed forward neural network,

a feedback neural network,

a self-organizing map,

a fuzzy logic system,

a random walk system,

a random forest system,

a probabilistic system,

a Bayesian system, or

a simulation system.

8. The system of claim 1 , wherein the RPA circuit is trained on the set of electronically recorded interactions with a set of user interfaces involved in a set of consolidation processes.

9. The system of claim 1 , wherein at least one of the set of loans is at least one of:

an auto loan,

an inventory loan,

a capital equipment loan,

a bond for performance,

a capital improvement loan,

a building loan,

a loan backed by an account receivable,

an invoice finance arrangement,

a factoring arrangement,

a pay day loan,

a refund anticipation loan,

a student loan,

a syndicated loan,

a title loan,

a home loan,

a venture debt loan,

a loan of intellectual property,

a loan of a contractual claim,

a working capital loan,

a small business loan,

a farm loan,

a municipal bond, or

a subsidized loan.

10. The system of claim 1 , wherein the RPA circuit includes at least one of:

a machine learning system,

a model-based system,

a rule-based system,

a deep learning system,

a hybrid system,

a neural network,

a convolutional neural network,

a feed forward neural network,

a feedback neural network,

a self-organizing map,

a fuzzy logic system,

a random walk system,

a random forest system,

a probabilistic system,

a Bayesian system, or

a simulation system.

11. The system of claim 1 , wherein managing the consolidation further includes managing at least one of:

identification of loans from a set of candidate loans,

negotiating a modification of a consolidation offer,

setting an interest rate,

deferring a payment requirement, or

closing a consolidation agreement.

12. A method for consolidating a set of loans, comprising:

collecting, via at least one processor, information about a set of loans;

collecting, via a set of data collection and monitoring services executing on the at least one processor, information about a set of loans, a condition of a collateral for the set of loans, and a set of electronically recorded interactions and outcomes between entities for a set of loan consolidation transactions;

monitoring, via the set of data collection and monitoring services, the condition of the collateral for the set of loans;

maintaining a training data set comprising the set of electronically recorded interactions and outcomes between the entities for the set of loan consolidation transactions;

communicating with the set of data collection and monitoring services to generate data on a blockchain of a distributed ledger corresponding to the information about the set of loans, the condition of the collateral for the set of loans as monitored by the set of data collection and monitoring services, and the set of electronically recorded interactions and the outcomes between the entities for the set of loan consolidation transactions;

training, via the at least one processor, an artificial intelligence circuit on the set of electronically recorded interactions;

classifying, using the artificial intelligence circuit, the set of loans as candidates for consolidation based on the set of electronically recorded interactions;

iteratively training, via the at least one processor, a robotic process automation (RPA) circuit using the training data set,

wherein the RPA circuit communicates with the artificial intelligence circuit to:

receive the condition of the collateral as monitored by the set of data collection and monitoring services from the blockchain data as accessed from the blockchain via a first application programming interface (API);

manage consolidation of at least a subset of the set of the classified loans on behalf of a party to one or more of the candidates for the consolidation based on an expected outcome of a consolidation activity that is predicted based on the condition of the collateral as monitored by the set of data collection and monitoring services, by:

automatically setting conditional steps and automatically executing the conditional steps based on the condition of the collateral as monitored by the set of data collection and monitoring services,

wherein the conditional steps include:

automatically facilitating, via a second API, a negotiation of a term of the set of loans; and

updating the training data set based on an outcome of the negotiation;

further training the RPA circuit on the updated training data set;

determining at least one of the outcome or a negotiating event of the negotiation associated with the consolidation;

recording, in the distributed ledger, the at least one of the outcome or the negotiating event; and

upon completion of the negotiation, automatically configuring a smart contract for a consolidated loan based on the outcome of the negotiation.

13. The method of claim 12 , further comprising:

negotiating the smart contract for at least one of the subset of the set of loans.

14. The method of claim 12 , wherein the set of electronically recorded interactions comprises a set of interactions between entities with a set of user interfaces involved in a set of consolidation processes.

15. The method of claim 12 , wherein collecting information about the set of loans comprises at least one of:

monitoring the entities using a set of Internet of Things;

pulling information related to the entities from publicly available information sites;

soliciting information related to the entities using crowdsourcing service;

pulling information related to the entities from publicly available information sites; or

providing a user interface for the entities to enter information.

16. An apparatus for consolidating a set of loans, comprising:

at least one processor;

a data collection and monitoring circuit that executes via the at least one processor and that collects information about a set of loans, a condition of a collateral for the set of loans, and a set of electronically recorded interactions and outcomes between entities for a set of loan consolidation activities,

wherein the data collection and monitoring circuit monitors the condition of the collateral for the set of loans, and

wherein the at least one processor maintains a training data set comprising the set of electronically recorded interactions and outcomes between the entities for the set of loan consolidation activities;

a blockchain service circuit to interface with a distributed ledger having a blockchain, wherein the blockchain service circuit communicates with the data collection and monitoring circuit to generate data on the blockchain corresponding to the information about the set of loans, the condition of the collateral for the set of loans as monitored by the data collection and monitoring circuit, and the set of electronically recorded interactions and the outcomes between the entities for the set of loan consolidation activities;

a machine learning circuit that executes via the at least one processor, that learns to classify the set of loans as candidates for consolidation by being trained on the set of electronically recorded interactions, and that classifies the set of loans as candidates for consolidation based on being trained on the set of electronically recorded interactions; and

a process automation circuit that executes via the at least one processor, that is trained, by the at least one processor, on the training data set, and wherein the process automation circuit communicates with the machine learning circuit to:

receive the condition of the collateral as monitored by the data collection and monitoring circuit from the blockchain data as accessed from the blockchain via a first application programming interface (API);

manage consolidation of at least a subset of the classified set of loans on behalf of a party to one or more of the candidates for the consolidation,

wherein the process automation circuit manages the consolidation based on an expected outcome of a consolidation activity that is predicted based on the condition of the collateral as monitored by the data collection and monitoring circuit, and

the process automation circuit further manages the consolidation by:

automatically setting conditional steps and automatically executing the conditional steps based on the condition of the collateral as monitored by the data collection and monitoring circuit,

wherein the conditional steps include:

automatically facilitating, via a second API, a negotiation of a term of the set of loans; and

updating the training data set based on an outcome of the negotiation,

wherein the at least one processor further trains the artificial intelligence component process automation circuit on the updated training data set,

wherein the at least one processor determines at least one of the outcome or a negotiating event of the negotiation associated with the consolidation, and records, in the distributed ledger, the at least one of the outcome or the negotiating event, and

wherein upon completion of the negotiation, the at least one processor automatically configures a smart contract for a consolidated loan based on the outcome of the negotiation.

17. The apparatus of claim 16 , wherein managing the consolidation of the subset of the classified set of loans further comprises:

negotiating the smart contract for at least one of the subset of classified set of loans.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 21, 2021
From: CELLA, CHARLES HOWARD
To: STRONG FORCE TX PORTFOLIO 2018, LLC
Reel/Frame 054990/0671 →
Continuity (12)
Continuation 16998668 · Aug 20, 2020
Continuation PCTUS2019058671 · Oct 29, 2019
Continuation In Part PCTUS2019030934 · May 6, 2019
Provisional Application 62843992 · May 6, 2019
Provisional Application 62843456 · May 5, 2019
Provisional Application 62843455 · May 5, 2019
Provisional Application 62818100 · Mar 13, 2019
Provisional Application 62787206 · Dec 31, 2018
Provisional Application 62751713 · Oct 29, 2018
Provisional Application 62751713 · Oct 29, 2018
Provisional Application 62667550 · May 6, 2018
Related Publication 20200394709A1 · Dec 17, 2020