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. 18, 2025

Filed:

Jun. 24, 2021
Applicant:

The Toronto-dominion Bank, Toronto, CA;

Inventors:

Ilya Stanevich, Toronto, CA;

Maxime Lafleur-Forcier, Boucherville, CA;

Xuling Wang, Toronto, CA;

Philippe Meunier, Montreal, CA;

Mathieu Jacob, Montreal, CA;

Robert Chamoun, Montreal, CA;

Bruno Veillete-Cossette, Montreal, CA;

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 5/04 (2023.01); G06N 20/00 (2019.01); G06Q 30/0204 (2023.01); G06Q 40/08 (2012.01);
U.S. Cl.
CPC ...
G06N 5/04 (2013.01); G06N 20/00 (2019.01); G06Q 30/0205 (2013.01); G06Q 40/08 (2013.01);
Abstract

A computing device for predicting an expected loss for a set of claim transactions is provided. The computing device predicts, at a first machine learning model, a claim frequency of the set of claim transactions over a given time period and trained using historical frequency data and based on a segment type defining a type of claim, each type of segment having peril types. The computing device also predicts, at a second machine learning model, claim severity of the set of claim transactions during the given time period, the second machine learning model trained using historical severity data and based on the segment type and the corresponding peril types. The computing device then determines the expected loss for the set of claim transactions over the given time period by applying a product of prediction of the first machine learning model and the second machine learning model.


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