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The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Patent No.:

US 12020307 B1

PDFFull Text
Date of Patent:
Jun. 25, 2024

Filed:

Aug. 31, 2022

Heuristic document verification and real time deposit engine

Applicant:

State Farm Mutual Automobile Insurance Company, Bloomington, IL (US);

Inventors:

Elizabeth A. Flowers, Bloomington, IL (US);

Puneit Dua, Bloomington, IL (US);

Eric Balota, Bloomington, IL (US);

Shanna L. Phillips, Bloomington, IL (US);

Assignee:

State Farm Mutual Automobile Insurance Company, Bloomington, IL (US);

Attorney:

Lee & Hayes, P.C.

Primary Examiner:

Frantzy Poinvil

Int. Cl.
CPC ...
G06Q 30/0601 (2023.01); G06F 40/30 (2020.01); G06N 3/006 (2023.01); G06N 5/01 (2023.01); G06N 5/04 (2023.01); G06N 20/00 (2019.01); G06Q 10/0631 (2023.01); G06Q 20/04 (2012.01); G06Q 20/24 (2012.01); G06Q 20/40 (2012.01); G06Q 30/01 (2023.01); G06Q 30/018 (2023.01); G06Q 40/02 (2023.01); G06Q 40/03 (2023.01); G06Q 40/12 (2023.01); H04M 3/22 (2006.01); H04M 3/51 (2006.01); H04W 12/08 (2021.01); G06Q 30/016 (2023.01);
U.S. Cl.
CPC ...
G06Q 30/0631 (2013.01); G06F 40/30 (2020.01); G06N 3/006 (2013.01); G06N 5/01 (2023.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); G06Q 10/06315 (2013.01); G06Q 10/06316 (2013.01); G06Q 20/042 (2013.01); G06Q 20/24 (2013.01); G06Q 20/4016 (2013.01); G06Q 30/01 (2013.01); G06Q 30/018 (2013.01); G06Q 40/02 (2013.01); G06Q 40/03 (2023.01); G06Q 40/12 (2013.12); H04M 3/2218 (2013.01); H04M 3/5175 (2013.01); H04M 3/5191 (2013.01); H04W 12/08 (2013.01); G06Q 30/016 (2013.01); H04M 2203/403 (2013.01);
Abstract

A heuristic engine includes capabilities to collect an unstructured data set, including document image data and correlate the image data with known valid data to detect document fraud. Notifications of fraud detection may include particular signature images, or characteristics of a document image. By feeding back indications of document fraud with correlations to past instances of fraud into the heuristic algorithm, the algorithm may learn and improve in fraud detection accuracy.

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