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:
Feb. 11, 2025

Filed:

Feb. 28, 2020
Applicant:

Mastercard Technologies Canada Ulc, Vancouver, CA;

Inventors:

John Hearty, Vancouver, CA;

Anton Laptiev, Vancouver, CA;

Hanhan Wu, Surrey, CA;

Carrie Ka Lai Cheung, Burnaby, CA;

Igor Opushnyev, New Westminster, CA;

Sik Suen Chan, Richmond, CA;

Parin Prashant Shah, Vancouver, CA;

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06Q 30/018 (2023.01); G06F 11/30 (2006.01); G06F 11/34 (2006.01); G06F 21/31 (2013.01); G06F 21/55 (2013.01); G06Q 10/10 (2023.01); G06Q 20/02 (2012.01); G06Q 20/40 (2012.01); G06Q 40/03 (2023.01); G06Q 50/26 (2024.01); H04L 9/40 (2022.01); H04L 67/50 (2022.01);
U.S. Cl.
CPC ...
G06Q 30/0185 (2013.01); G06F 11/302 (2013.01); G06F 11/3438 (2013.01); G06F 21/316 (2013.01); G06F 21/554 (2013.01); G06Q 10/10 (2013.01); G06Q 20/027 (2013.01); G06Q 20/40145 (2013.01); G06Q 20/4016 (2013.01); G06Q 20/4093 (2013.01); G06Q 20/4097 (2013.01); G06Q 40/03 (2023.01); G06Q 50/265 (2013.01); H04L 63/1425 (2013.01); H04L 63/1433 (2013.01); H04L 67/535 (2022.05);
Abstract

A fraud prevention system that includes a fraud prevention server including an electronic processor and a memory. The memory includes an online application origination (OAO) service. When executing the OAO service, the electronic processor is configured to determine whether the OAO service is enabled and whether a website configuration includes a list of multi-page placements for an online application, determine that input data needs to be stored in the memory and combined into multi-page input data, determine a fraud risk score of the online application based on the multi-page input data and an online application origination (OAO) model that differentiates between a behavior of a normal user and a behavior of a nefarious actor during a submission of the online application on a device, and control a client server to approve, hold, or deny the online application based on the fraud risk score that is determined.


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