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:
Oct. 31, 2023

Filed:

Sep. 08, 2021
Applicant:

Fair Isaac Corporation, Roseville, MN (US);

Inventors:

Gerald Fahner, Austin, TX (US);

Brad Vancho, San Francisco, CA (US);

Assignee:

FAIR ISAAC CORPORATION, Minneapolis, MN (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 10/06 (2023.01); G06Q 30/02 (2023.01); G16H 50/20 (2018.01); G06N 20/20 (2019.01); G16H 50/30 (2018.01); G06Q 10/0637 (2023.01); G06Q 10/0635 (2023.01); G06Q 40/03 (2023.01);
U.S. Cl.
CPC ...
G16H 50/20 (2018.01); G06N 20/20 (2019.01); G06Q 10/0635 (2013.01); G06Q 10/06375 (2013.01); G06Q 40/03 (2023.01); G16H 50/30 (2018.01);
Abstract

A sensitivity index model for predicting the sensitivity of an entity to a potential future disruption can be trained using a process that includes dividing a population of entities for which data attributes are available into matched pairs in a first sub-population and a second sup-population based on matching propensity scores for the entities using supervised machine learning, modeling outcomes for the two sub-populations, using the resultant models to calculate expected performances of the entities under differing conditions, and generating the sensitivity index model using supervised learning techniques based on quantification of differences between the calculated expected performances for the entities.


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