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. 30, 2024

Filed:

Aug. 10, 2022
Applicant:

Capital One Services, Llc, McLean, VA (US);

Inventors:

Peter Tanski, Marlborough, MA (US);

Matthew Peroni, Bedford, MA (US);

Deny Daniel, Medford, MA (US);

Ranjith Zachariah, Waltham, MA (US);

Viji Soundar, Richmond, VA (US);

Paul Vest, Bumpass, VA (US);

Kevin Zhang, Braintree, MA (US);

Assignee:

Capital One Services, LLC, McLean, VA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 17/00 (2019.01); G06F 40/211 (2020.01); G06F 40/295 (2020.01); G06F 40/40 (2020.01); G06Q 10/0635 (2023.01);
U.S. Cl.
CPC ...
G06Q 10/0635 (2013.01); G06F 40/211 (2020.01); G06F 40/295 (2020.01); G06F 40/40 (2020.01);
Abstract

Embodiments disclosed are directed to a computing system that performs steps to automatically identify risk control features and entities in a risk control document. The computing system uses a generative machine learning (ML) model to transform a risk control document into sequences of words, classify risk control features associated with the sequences of words, and pair the sequences of words with the classified risk control features. The computing system then uses a natural language processing (NLP) model to identify syntactic characteristics of the sequences of words. Subsequently, the computing system uses a discriminative predictor system to correct the classified risk control features based on the identified syntactic characteristics, identify boundaries of the corrected classified risk control features, and pair the identified boundaries with the corrected classified risk control features.


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