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:
Jul. 23, 2024

Filed:

May. 10, 2023
Applicant:

Visa International Service Association, San Francisco, CA (US);

Inventors:

Juharasha Shaik, Fremont, CA (US);

Durga Kala, Cupertino, CA (US);

Gajanan Chinchwadkar, Fremont, CA (US);

Assignee:

Visa International Service Association, San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2023.01); G06F 9/50 (2006.01); G06F 18/213 (2023.01); G06F 18/214 (2023.01); G06F 21/60 (2013.01); G06N 3/045 (2023.01); G06F 9/46 (2006.01);
U.S. Cl.
CPC ...
G06F 21/604 (2013.01); G06F 9/5027 (2013.01); G06F 18/213 (2023.01); G06F 18/214 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06F 9/466 (2013.01);
Abstract

A method includes receiving historical interaction data, which includes a plurality of historical interactions. Each historical interaction is associated with a plurality of data fields. The method includes assigning a plurality of weights to the plurality of data fields, generating a neural network using the plurality of weights and the plurality of data fields, identifying a first plurality of feature indicators indicative of a first class, the first class being different from a second class; receiving a second plurality of feature indicators derived from data relating to compromised accounts, updating, a probability distribution component using the first plurality of feature indicators and the second plurality of feature indicators, and receiving current data for an interaction. The method also includes applying the probability distribution component to the current data, and scoring the interaction using the probability distribution component.


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