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:
Aug. 12, 2025

Filed:

Dec. 22, 2021
Applicant:

Fidelity Information Services, Llc, Jacksonville, FL (US);

Inventors:

Benjamin Wellmann, Boca Raton, FL (US);

Gary Duma, Royal Oak, MI (US);

Geoffrey Allan Sparke, Workington, GB;

Brandon A. Castro, Jacksonville, FL (US);

Assignee:

Fidelity Information Services, LLC, Jacksonville, FL (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 10/06 (2023.01); G06F 18/21 (2023.01); G06N 20/00 (2019.01); G06Q 10/0635 (2023.01); G06Q 10/0637 (2023.01);
U.S. Cl.
CPC ...
G06Q 10/06375 (2013.01); G06F 18/217 (2023.01); G06N 20/00 (2019.01); G06Q 10/0635 (2013.01);
Abstract

A method for improving the quality of a machine-learning based model includes generating a first query requesting a description of a change proposed to a system and an intended outcome of the change proposed; receiving a first response; generating a second query providing a risk of an incident associated with the change proposed and requesting justification of the change proposed in view of the risk; receiving a second response; generating a third query requesting an implementation plan for the change proposed; receiving a third response; generating an alert to an incident owner providing the description, intended outcome, risk, justification, and implementation plan of the change proposed; receiving a risk confirmation or rejection from the incident owner confirming or rejecting a relationship between the change proposed and the risk; and updating the machine-learning based model to learn an association between extracted features of the change and extracted features of the incident.


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