US 11,748,822 B2
Systems and methods for automatically restructuring debt
Charles Howard Cella, Pembroke, MA (US)
Assigned to Strong Force TX Portfolio 2018, LLC, Fort Lauderdale, FL (US)
Filed by Strong Force TX Portfolio 2018, LLC, Fort Lauderdale, FL (US)
Filed on May 28, 2020, as Appl. No. 16/886,616.
Application 16/886,616 is a continuation of application No. 16/803,387, filed on Feb. 27, 2020, granted, now 11,610,261.
Application 16/803,387 is a continuation of application No. PCT/US2019/058647, filed on Oct. 29, 2019.
Application PCT/US2019/058647 is a continuation in part of application No. PCT/US2019/030934, filed on May 6, 2019.
Application PCT/US2019/058647 is a continuation in part of application No. PCT/US2019/030934, filed on May 6, 2019.
Claims priority of provisional application 62/843,992, filed on May 6, 2019.
Claims priority of provisional application 62/843,455, filed on May 5, 2019.
Claims priority of provisional application 62/843,456, filed on May 5, 2019.
Claims priority of provisional application 62/818,100, filed on Mar. 13, 2019.
Claims priority of provisional application 62/787,206, filed on Dec. 31, 2018.
Claims priority of provisional application 62/751,713, filed on Oct. 29, 2018.
Claims priority of provisional application 62/667,550, filed on May 6, 2018.
Prior Publication US 2020/0294134 A1, Sep. 17, 2020
This patent is subject to a terminal disclaimer.
Int. Cl. G06Q 40/02 (2012.01); G06Q 10/10 (2012.01); G06Q 30/02 (2012.01); G06N 20/00 (2019.01); G06Q 30/00 (2012.01); G06Q 40/08 (2012.01); G06F 9/54 (2006.01); G06F 16/27 (2019.01); G06F 16/23 (2019.01); G06Q 50/18 (2012.01); G06Q 50/26 (2012.01); G06Q 50/00 (2012.01); G06Q 30/0208 (2023.01); G06Q 30/0207 (2023.01); G06N 3/08 (2023.01); G06Q 30/0201 (2023.01); G06F 9/46 (2006.01); G06Q 10/0639 (2023.01); G06Q 20/40 (2012.01); H04L 9/06 (2006.01); G06N 5/04 (2023.01); G06Q 30/018 (2023.01); G16Y 10/50 (2020.01); G16Y 40/10 (2020.01); G06F 18/22 (2023.01); G06F 18/23 (2023.01); G06F 18/241 (2023.01); G06Q 40/03 (2023.01); G06N 3/042 (2023.01); G06V 10/762 (2022.01); G06Q 40/04 (2012.01)
CPC G06Q 50/01 (2013.01) [G06F 9/466 (2013.01); G06F 9/543 (2013.01); G06F 16/2379 (2019.01); G06F 16/27 (2019.01); G06F 18/22 (2023.01); G06F 18/23 (2023.01); G06F 18/241 (2023.01); G06N 3/042 (2023.01); G06N 3/08 (2013.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); G06Q 10/0639 (2013.01); G06Q 10/10 (2013.01); G06Q 20/405 (2013.01); G06Q 30/018 (2013.01); G06Q 30/0201 (2013.01); G06Q 30/0206 (2013.01); G06Q 30/0208 (2013.01); G06Q 30/0215 (2013.01); G06Q 30/0278 (2013.01); G06Q 40/03 (2023.01); G06Q 40/08 (2013.01); G06Q 50/18 (2013.01); G06Q 50/188 (2013.01); G06Q 50/26 (2013.01); G06V 10/762 (2022.01); G16Y 10/50 (2020.01); G16Y 40/10 (2020.01); H04L 9/0637 (2013.01); G06Q 40/04 (2013.01); G06Q 2220/18 (2013.01)] 21 Claims
OG exemplary drawing
 
1. A system, comprising: a blockchain service circuit structured to interface with a distributed ledger, the blockchain service circuit comprising a first application programming interface (API) configured to communicate with the distributed ledger; a data collection circuit structured to monitor and collect information about at least one entity involved in a loan from the blockchain service circuit via a second API, the monitored and collected information including blockchain data from the distributed ledger; and a smart contract circuit structured to automatically restructure a debt related to the loan based on the monitored and collected information about the at least one entity involved in the loan, the debt being secured by at least one item of collateral, the smart contract circuit comprising at least one of an artificial intelligence system, a machine learning system, or a neural network, the at least one of the artificial intelligence system, the machine learning system, or the neural network being configured to: maintain a training data set comprising feedback data of outcomes of success comprising recognition of a pattern of prices or value of the item of collateral over time in relation to a collateral satisfaction value; and iteratively train the at least one of the artificial intelligence system, the machine learning system, or the neural network, using the training data set, to: receive the blockchain data via the first API; and output an action value corresponding to a loan-related activity based on the item of collateral, the loan-related activity comprising at least one of validating title for the item of collateral, recording a change in title for the item of collateral, assessing the value of the one of the item of collateral, initiating inspection of the one of the item of collateral, initiating maintenance of the item of collateral, initiating security for the item of collateral, modifying terms and conditions for the item of collateral, offering the loan, accepting the loan, underwriting the loan, setting an interest rate for a loan, deferring a payment requirement, modifying the interest rate for the loan, calling the loan, closing the loan, setting terms and conditions for the loan, providing notices required to be provided to a borrower, foreclosing on property subject to the loan, or modifying terms and conditions for the loan; automatically implement the loan-related activity corresponding to the action value in response to the collateral satisfaction value via a third API; automatically restructure the debt based on an outcome of the automatically implementing the loan-related activity; generate one or more blocks containing data corresponding to the loan-related activity and the automatic restructure of the debt; generate one or more hash values of the one or more blocks; and link the one or more blocks to the blockchain via the one or more hash values via a third API.