Methods and systems for deconflicting data from multiple sources in computer systems

Patent metadata

Field	Value
Publication number	US-12561656-B2
Application number	US-202418593277-A
Country	US
Kind code	B2
Filing date	Mar 1, 2024
Priority date	May 15, 2020
Publication date	Feb 24, 2026
Grant date	Feb 24, 2026

Abstract

Methods and systems are described for verifying an identity of a user through contextual knowledge-based authentication. The system described uses contextual knowledge-based authentication. By verifying an identity of a user through contextual knowledge-based authentication, the verification is both more secure and more intuitive to the user. For example, by relying on confidential and/or proprietary information, the system may generate verification questions, the answers to which are known only by the user.

First claim

What is claimed is:

1 . A system for aggregating user data from a plurality of sources, the system comprising:
one or more processors; and one or more non-transitory computer-readable mediums comprising instructions recorded thereon that when executed by the one or more processors cause operations comprising:
receiving a first user input to aggregate record data of a user;
in response to the first user input, retrieving first user record data and a third user record data from a first network and second user record data and a fourth user record data from a second network, wherein the first user record data and the third user record data is encoded in a first format and the second user record data and the fourth user record data is encoded in a second format;
extracting first source data from the first user record data;
extracting third source data from the third user record data;
extracting second source data from the second user record data;
extracting fourth source data from the fourth user record data;
retrieving a first source data category value from the first source data;
retrieving a second source data category value from the second source data;
retrieving a third source data category value from the third source data;
retrieving a fourth source data category value from the fourth source data;
comparing the first source data category value to the second source data category value;
in response to determining that the first source data category value and the second source data category value correspond, deduplicating the first user record data and the second user record data in a list of aggregated record data of the user;
comparing the third source data category value to the fourth source data category value; and
in response to determining that the third source data category value and the fourth source data category value do not correspond, generating for display, in the list of aggregated record data, third user record data and the fourth user record data.

2 . A method for aggregating user data from a plurality of sources while mitigating duplicate entries, the method comprising:
receiving, via a user interface, a first user input to access an aggregation service that aggregates record data of a user; in response to the first user input, retrieving first user record data from a first network and second user record data from a second network, wherein the first user record data is encoded in a first format and the second user record data is encoded in a second format; extracting first source data from the first user record data; extracting second source data from the second user record data; retrieving a first source data category value from the first source data; retrieving a second source data category value from the second source data; comparing the first source data category value to the second source data category value; in response to determining that the first source data category value and the second source data category value correspond, determining to deduplicate the first user record data and the second user record data in a list of aggregated record data of the user; and generating for display, in the user interface, the list of aggregated record data of the user.

3 . The method of claim 2 , further comprising:
extracting third source data from third user record data; extracting fourth source data from fourth user record data; retrieving a third source data category value from the third source data; retrieving a fourth source data category value from the fourth source data; comparing the third source data category value to the fourth source data category value; and in response to determining that the third source data category value and the fourth source data category value do not correspond, generating for display, in the user interface, the list of aggregated record data with the third user record data and the fourth user record data.

4 . The method of claim 2 , further comprising:
crowd-sourcing a user query to a plurality of other users based on respective user record data for the plurality of other users, wherein the user query includes the first source data or the second source data; and aggregating responses from the plurality of other users.

5 . The method of claim 4 , wherein crowd-sourcing the user query to the plurality of other users based on respective user record data for the plurality of other users, further comprises:
retrieving a threshold time period; determining whether the respective user record data is from the threshold time period; and selecting the plurality of other users based on the respective user record data corresponding to the threshold time period.

6 . The method of claim 5 , further comprising:
selecting a number of the plurality of other users based on a percentage of users with user record data that includes the first source data or the second source data; and determining a number of user queries based on the number of the plurality of other users.

7 . The method of claim 2 , wherein determining to deduplicate the first user record data and the second user record data in the list of aggregated record data of the user further comprises:
generating for display a user query to resolve a conflict between the first source data and the second source data, wherein the user query includes a user selectable option for resolving the conflict in favor of the first source data or the second source data; and receiving a second user input responding to the user query.

8 . The method of claim 2 , wherein comparing the first source data category value to the second source data category value further comprises:
determining a network name for the first source data category value or the second source data category value; and using the network name to compare the first user record data to the second user record data.

9 . The method of claim 2 , wherein comparing the first source data category value to the second source data category value further comprises:
determining a network name for the first source data category value; and using the network name to compare the first user record data to the second user record data.

10 . The method of claim 2 , wherein comparing the first source data category value to the second source data category value further comprises:
determining a naming convention for the first source data category value; and using the naming convention to compare the first user record data to the second user record data.

11 . The method of claim 2 , wherein comparing the first source data category value to the second source data category value further comprises:
determining a similarity metric between the first source data category value and the second source data category value; and using the similarity metric to determine that the first source data category value and the second source data category value correspond.

12 . The method of claim 2 , wherein the first format is specific to the first network and the second format is specific to the second network.

13 . The method of claim 2 , wherein the first source data category value includes an amount value, a time stamp value, a source address value, a source name value, or a network name value.

14 . The method of claim 2 , wherein comparing the first source data category value to the second source data category value further comprises applying a fuzzy string matching algorithm that:
removes numerals and special characters from the first source data category value from the first source data and the first source data category value from the s

Assignees

• Capital One Services Llc

Inventors

• Edwards Joshua
• Benkreira Abdelkader M'Hamed
• Mossoba Michael

Classifications

• G06Q20/40

  Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists · CPC title

• G06Q20/341

  Active cards, i.e. cards including their own processing means, e.g. including an IC or chip · CPC title

• G07F7/1008

  Active credit-cards provided with means to personalise their use, e.g. with PIN-introduction/comparison system · CPC title

• G06Q20/04

  Payment circuits · CPC title

• G06Q20/24

  Credit schemes, i.e. "pay after" · CPC title