US 12,002,090 B2
Approving and updating dynamic mortgage applications
Benjamin Tarmann, Normal, IL (US); Richard R. Rhodes, Tacoma, WA (US); Lokesh Awasthy, Santa Clara, CA (US); Denise DeRoeck, Bloomington, IL (US); Jaime Skaggs, Chenoa, IL (US); Jacob J. Alt, Downs, IL (US); Shanna L. Phillips, Bloomington, IL (US); Shyam Tummala, Bloomington, IL (US); Matthew S Meierotto, Bloomington, IL (US); Richard D Groonwald, Bloomington, IL (US); and Brian J. Hughes, Scottsdale, AZ (US)
Assigned to State Farm Mutual Automobile Insurance Company, Bloomington, IL (US)
Filed by State Farm Mutual Automobile Insurance Company, Bloomington, IL (US)
Filed on Dec. 23, 2021, as Appl. No. 17/560,938.
Application 17/560,938 is a continuation of application No. 15/975,156, filed on May 9, 2018, granted, now 11,210,734.
Claims priority of provisional application 62/581,292, filed on Nov. 3, 2017.
Claims priority of provisional application 62/535,018, filed on Jul. 20, 2017.
Claims priority of provisional application 62/514,470, filed on Jun. 2, 2017.
Claims priority of provisional application 62/504,328, filed on May 10, 2017.
Prior Publication US 2022/0114663 A1, Apr. 14, 2022
Int. Cl. G06Q 40/03 (2023.01); G06Q 30/02 (2023.01); G06Q 50/16 (2012.01); H04L 9/00 (2022.01); H04L 9/06 (2006.01)
CPC G06Q 40/03 (2023.01) [G06Q 30/0278 (2013.01); G06Q 50/16 (2013.01); H04L 9/0637 (2013.01); G06Q 2220/00 (2013.01); H04L 9/50 (2022.05)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
maintaining a blockchain associated with a mortgage application of a customer, wherein maintaining the blockchain includes providing access to the blockchain to a plurality of authorized entities associated with the mortgage application;
storing, on the blockchain, a first amount for which the customer is approved for a mortgage loan;
after storing the first amount on the blockchain, monitoring the blockchain, using a trained machine-learned model, to determine updated information associated with the customer added to the blockchain by one or more of the authorized entities;
determining, based at least in part on an output of the trained machine-learned model, an absence of an increased risk event associated with the customer;
calculating, in response to determining the absence of the increased risk event and based at least in part on the updated information, an updated amount for which the customer is approved for the mortgage loan;
compiling a new block for the blockchain including the updated amount, wherein compiling the new block includes computing a hash value associated with the new block, using a cryptographic hash function; and
updating the blockchain to include the new block, wherein updating the blockchain includes cryptographically linking the new block to a previous block in the blockchain.