IP Library › Granted Patent US 12,683,960
Granted Patent B2
US 12,683,960 · App. 18/884,552 · Granted Jul 14, 2026

Email processing for improved authentication question accuracy

Inventors: Viraj Chaudhary (Katy, TX); Vyjayanthi Vadrevu (Pflugerville, TX); Tyler Maiman (Melville, NY); David Septimus (New York, NY); Samuel Rapowitz (Roswell, GA); Jenny Melendez (Falls Church, VA); Joshua Edwards (Philadelphia, PA)
Assignee: Capital One Services, LLC
H04L63/0876G06F18/214G06N20/00G06Q10/107H04L63/102H04L63/123
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Quick Facts
Patent No.
US 12,683,960
App. No.
18/884,552
Filed
Sep 13, 2024
Granted
Jul 14, 2026
Kind
B2
Art Unit
2494
USPC
726/4
Abstract

Methods, systems, and apparatuses are described herein for improving the accuracy of authentication questions using e-mail processing. A request for access to an account may be received from a user device. A plurality of organizations may be identified. One or more e-mail associated with the account may be identified. The e-mails may be processed to identify one or more organizations that correspond to transactions conducted by a user. A modified plurality of organizations may be generated by removing, from the plurality of organizations, the one or more organizations. An authentication question may be generated and provided to the user device. A response to the authentication question may be received, and the user device may be provided access based on the response.

Claims (64)

1 . A method comprising:

receiving, from an e-mail server, one or more e-mails associated with an account associated with a user;

identifying one or more e-mail templates corresponding to a plurality of organizations indicated by an organizations database;

processing, based on the one or more e-mail templates, the one or more e-mails to identify at least one e-mail associated with one or more organizations of the plurality of organizations;

generating a modified plurality of organizations by removing, from the plurality of organizations, the one or more organizations;

generating an authentication question related to at least one of the modified plurality of organizations; and

providing, based on a response to the authentication question, a user device access to the account.

2 . The method of claim 1 , wherein processing the one or more e-mails to identify the one or more organizations comprises:

identifying, based on comparing at least one of the one or more e-mail templates to at least one of the one or more e-mails, a second organization.

3 . The method of claim 1 , wherein processing the one or more e-mails to identify the one or more organizations comprises:

training, using input data comprising a plurality of e-mails with tagged organizations, a machine learning model to identify indicators of organizations in e-mail data;

providing, as input to the machine learning model, the one or more e-mails; and

receiving, as output from the machine learning model, an indication of the one or more organizations.

4 . The method of claim 1 , further comprising:

identifying, based on the one or more e-mails, a good or service, wherein generating the authentication question is based on the good or service.

5 . The method of claim 1 , further comprising:

identifying, based on the one or more e-mails, an average expenditure associated with the user, wherein generating the authentication question is based on the average expenditure.

6 . The method of claim 1 , wherein identifying the plurality of organizations comprises:

randomly selecting, from the organizations database, a predetermined quantity of organizations.

7 . The method of claim 1 , further comprising:

identifying one or more aliases associated with the one or more organizations, wherein generating the modified plurality of organizations comprises removing, from the plurality of organizations and based on the one or more aliases, at least one of the plurality of organizations.

8 . The method of claim 1 , wherein receiving the one or more e-mails associated with the account comprises:

querying the e-mail server for e-mails associated with a time period.

9 . The method of claim 1 , wherein removing the one or more organizations comprises:

determining that a quantity of the modified plurality of organizations satisfies a threshold; and

adding, to the modified plurality of organizations, indicators of additional organizations.

10 . A computing device comprising:

one or more processors; and

memory storing instructions that, when executed by the one or more processors, cause the computing device to:

receive, from an e-mail server, one or more e-mails associated with an account associated with a user;

identify one or more e-mail templates corresponding to a plurality of organizations indicated by an organizations database;

process, based on the one or more e-mail templates, the one or more e-mails to identify at least one e-mail associated with one or more organizations of the plurality of organizations;

generate a modified plurality of organizations by removing, from the plurality of organizations, the one or more organizations;

generate an authentication question related to at least one of the modified plurality of organizations; and

provide, based on a response to the authentication question, a user device access to the account.

11 . The computing device of claim 10 , wherein the instructions, when executed by the one or more processors, cause the computing device to process the one or more e-mails to identify the one or more organizations by causing the computing device to:

identify, based on comparing at least one of the one or more e-mail templates to at least one of the one or more e-mails, a second organization.

12 . The computing device of claim 10 , wherein the instructions, when executed by the one or more processors, cause the computing device to process the one or more e-mails to identify the one or more organizations by causing the computing device to:

train, using input data comprising a plurality of e-mails with tagged organizations, a machine learning model to identify indicators of organizations in e-mail data;

provide, as input to the machine learning model, the one or more e-mails; and

receive, as output from the machine learning model, an indication of the one or more organizations.

13 . The computing device of claim 10 , wherein the instructions, when executed by the one or more processors, cause the computing device to:

identify, based on the one or more e-mails, a good or service, wherein the instructions, when executed by the one or more processors, cause the computing device to generate the authentication question based on the good or service.

14 . The computing device of claim 10 , wherein the instructions, when executed by the one or more processors, cause the computing device to:

identify, based on the one or more e-mails, an average expenditure associated with the user, wherein the instructions, when executed by the one or more processors, cause the computing device to generate the authentication question based on the average expenditure.

15 . The computing device of claim 10 , wherein the instructions, when executed by the one or more processors, cause the computing device to identify the plurality of organizations by causing the computing device to:

randomly select, from the organizations database, a predetermined quantity of organizations.

16 . One or more non-transitory computer-readable media storing instructions that, when executed by one or more processors, cause a computing device to:

receive, from an e-mail server, one or more e-mails associated with an account associated with a user;

identify one or more e-mail templates corresponding to a plurality of organizations indicated by an organizations database;

process, based on the one or more e-mail templates, the one or more e-mails to identify at least one e-mail associated with one or more organizations of the plurality of organizations;

generate a modified plurality of organizations by removing, from the plurality of organizations, the one or more organizations;

generate an authentication question related to at least one of the modified plurality of organizations; and

provide, based on a response to the authentication question, a user device access to the account.

17 . The computer-readable media of claim 16 , wherein the instructions, when executed by the one or more processors, cause the computing device to process the one or more e-mails to identify the one or more organizations by causing the computing device to:

identify, based on comparing at least one of the one or more e-mail templates to at least one of the one or more e-mails, a second organization.

18 . The computer-readable media of claim 16 , wherein the instructions, when executed by the one or more processors, cause the computing device to process the one or more e-mails to identify the one or more organizations by causing the computing device to:

train, using input data comprising a plurality of e-mails with tagged organizations, a machine learning model to identify indicators of organizations in e-mail data;

provide, as input to the machine learning model, the one or more e-mails; and

receive, as output from the machine learning model, an indication of the one or more organizations.

19 . The computer-readable media of claim 16 , wherein the instructions, when executed by the one or more processors, cause the computing device to:

identify, based on the one or more e-mails, a good or service, wherein the instructions, when executed by the one or more processors, cause the computing device to generate the authentication question based on the good or service.

20 . The computer-readable media of claim 16 , wherein the instructions, when executed by the one or more processors, cause the computing device to:

identify, based on the one or more e-mails, an average expenditure associated with the user, wherein the instructions, when executed by the one or more processors, cause the computing device to generate the authentication question based on the average expenditure.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 17, 2024
From: CHAUDHARY, VIRAJ; VADREVU, VYJAYANTHI; MAIMAN, TYLER; SEPTIMUS, DAVID; RAPOWITZ, SAMUEL; MELENDEZ, JENNY; EDWARDS, JOSHUA
To: CAPITAL ONE SERVICES, LLC
Reel/Frame 068608/0457 →
Continuity (3)
Continuation 18243334 · Sep 7, 2023
Continuation 17314690 · May 7, 2021
Related Publication 20250016156A1 · Jan 9, 2025
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