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.

Date of Patent:
Dec. 21, 2021

Filed:

Jan. 03, 2018
Applicant:

Qcash Financial, Llc, Olympia, WA (US);

Inventors:

Steve Way, Sherwood, OR (US);

Ben Morales, Olympia, WA (US);

Heidi Tinsley, Tumwater, WA (US);

Mark Baumgartner, Olympia, WA (US);

Assignee:

QCASH FINANCIAL, LLC, Olympia, WA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06Q 40/00 (2012.01); G06Q 40/02 (2012.01); G06F 17/18 (2006.01); G06N 5/04 (2006.01);
U.S. Cl.
CPC ...
G06Q 40/025 (2013.01); G06F 17/18 (2013.01); G06N 5/04 (2013.01); G06Q 40/12 (2013.12);
Abstract

This disclosure describes techniques for determining whether to approve or deny a borrower's lending-product request by selectively using a heuristic and statistical model. More specifically, a borrower may submit a lending-product request to a Heuristic-Statistical Risk Management (HS-RM) system, and in doing so the HS-RM system may analyze relationship attributes of the borrower to determine a likelihood of borrower repaying a loan over a predetermined time period, and avoid being charged off. In some examples, the HS-RM system may execute a plurality of statistical models to determine a charge-off probability score. Each statistical model may be based on a set, or subset of historical lending-product data. A subset of historical lending-product data may be based on a selection bias of shared characteristics within a set of historical lending-product data. The selection bias may be based on characteristics of a lending-product request or relationship attributes of a borrower.


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