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. 22, 2024

Filed:

May. 04, 2020
Applicant:

Actimize Ltd., Ra'anana, IL;

Inventors:

Amir Shachar, Ramat Gan, IL;

Einat Neumann Ben Ari, Hod Hasharon, IL;

Danny Butvinik, Haifa, IL;

Yoav Avneon, Ness-Ziona, IL;

Gabrielle Zaghdoun Azoulay, Tel Aviv, IL;

Liat Elboim, Rishon Lezion, IL;

Assignee:

ACTIMIZE LTD., Ra'anana, IL;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 20/20 (2019.01); G06F 21/60 (2013.01); G06N 20/00 (2019.01); G06Q 20/40 (2012.01); G06F 21/62 (2013.01);
U.S. Cl.
CPC ...
G06N 20/20 (2019.01); G06N 20/00 (2019.01); G06Q 20/4016 (2013.01); G06F 21/60 (2013.01);
Abstract

An artificial intelligence system configured to detect anomalies in transaction data sets. The system includes a processor and a computer readable medium operably coupled thereto, the computer readable medium comprising a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, to perform modeling operations which include receiving a first data set for training a first machine learning model to detect anomalies in the transaction data sets using a machine learning technique, accessing at least one micro-model trained using at least one second data set separate from the first data set, determining risk scores from the first data set using the at least one micro-model, enriching the first data set with the risk scores, and determining the first machine learning model for the enriched first data set using the machine learning technique.


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