Method and system for identifying account duplication in data management systems

Patent metadata

Field	Value
Publication number	US-11093462-B1
Application number	US-201816116558-A
Country	US
Kind code	B1
Filing date	Aug 29, 2018
Priority date	Aug 29, 2018
Publication date	Aug 17, 2021
Grant date	Aug 17, 2021

Abstract

A method and system of identifying account duplication in data management systems utilizes a dual-phase approach, consisting of a projection phase and a clustering phase. In the projection phase, user account and transaction data is obtained and grouped into transactions entities. These transactions entities are then processed to create transactions entity projections. In the clustering phase, the transactions entity projections are grouped and aggregated according to specified parameters, which results in the generation of transactions graphs. The data from the transactions graphs is processed and analyzed to generate reliable indicators representing the presence or absence of account duplication in a data management system.

First claim

What is claimed is:

1. A method for identifying account duplication, the method performed by one or more processors of a computer-implemented system and comprising:
obtaining, from one or more users, user credential data associated with one or more user account providers;
obtaining, from the one or more user account providers, using the user credential data, user account and transaction data associated with one or more user accounts;
selecting, from a group of parameters that define the user account and transaction data, one or more transaction grouping parameters;
defining, using the selected transaction grouping parameters, one or more transactions entities for the one or more user accounts;
selecting one or more entity projection parameters to represent the one or more transactions entities;
generating, using the user account and transaction data in the one or more transactions entities, one or more projections for the one or more transactions entities, based on the selected entity projection parameters;
generating, using the user account and transaction data in the one or more transactions entities and projection data in the one or more projections, a transactions entity projection table for one or more transactions entity projections;
selecting, from a group of parameters that define the data in the transactions entity projection table, one or more clustering parameters;
processing the data in the transactions entity projection table to identify user accounts with matching clustering parameter values;
generating a matched accounts table for the user accounts with matching clustering parameter values;
processing data from the matched accounts table to generate data representing one or more bi-directional transactions graphs; and
utilizing data representing at least part of the one or more bi-directional transactions graphs to determine a likelihood of account duplication between any of the one or more user accounts.

2. The method of claim 1 , wherein the group of parameters include one or more of:
a set of user credentials associated with a user and a user account provider;
a credential set ID associated with a set of user credentials;
an account name associated with a user account;
an account number associated with a user account;
an account ID associated with a user account;
an account balance associated with a user account;
a name of a user associated with a user account;
an address a user associated with a user account;
a billing data a user associated with a user account;
an amount of each transaction associated with a user account;
a posted transaction date of each transaction associated with a user account;
a name of the payee for each transaction associated with a user account; and
an address of the payee for each transaction associated with a user account.

3. The method of claim 1 , wherein the selected transaction grouping parameters include one or more of:
a credential set ID associated with a set of user credentials;
an account ID associated with a user account; and
the posted transaction date of each transaction associated with a user account.

4. The method of claim 1 , wherein defining one or more transactions entities for one or more user accounts includes:
grouping the user account and transaction data into one or more groups according to the selected transaction grouping parameters; and
defining the one or more transactions entities as a collection of all user account and transactional data found in each of the one or more groups, as grouped according to the selected transaction grouping parameters.

5. The method of claim 1 , wherein the selected entity projection parameters include one or more of:
a number of transactions in each of the transactions entities;
a mean of the transaction amounts in each of the transactions entities; and
a standard deviation of the transaction amounts in each of the transactions entities.

6. The method of claim 1 , wherein generating the one or more projections for the one or more transactions entities includes:
processing the user transaction data from individual transactions within each of the one or more transactions entities in accordance with selected entity projection parameters.

7. The method of claim 6 , wherein processing the user transaction data in accordance with the selected entity projection parameters includes one or more of:
calculating a number of transactions in a given transactions entity;
calculating a mean of the transaction amounts in a given transactions entity; and
calculating a standard deviation of the transaction amounts in a given transactions entity.

8. The method of claim 1 , wherein generating a transactions entity projection table for the one or more transactions entity projections comprise includes:
aggregating user account and transaction data from the one or more transactions entities and the projection data into a transactions entity projection table.

9. The method of claim 8 , wherein the transactions entity projection table includes:
one row for each of the transactions entity projections;
one column for each of the selected transaction grouping parameters; and
one column for each of the selected entity projection parameters.

10. The method of claim 9 , wherein the selected transaction grouping parameters include one or more of:
a credential set ID associated with a set of user credentials;
an account ID associated with a user account; and
the posted transaction date of each transaction associated with a user account.

11. The method of claim 9 , wherein the selected entity projection parameters include one or more of:
a number of transactions in each of the transactions entities;
a mean of the transaction amounts in each of the transactions entities; and
a standard deviation of the transaction amounts in each of the transactions entities.

12. The method of claim 1 , wherein the one or more clustering parameters are selected from a group of parameters comprising including one or more of the selected transaction grouping parameters and one or more of the selected entity projection parameters.

13. The method of claim 12 , wherein the selected clustering parameters include one or more of:
a credential set ID associated with a set of user credentials;
a posted transaction date of each transaction associated with a user account;
a number of transactions in each of the transactions entities;
a mean of the transaction amounts in each of the transactions entities; and
a standard deviation of the transaction amounts in each of the transactions entities.

14. The method of claim 1 , wherein processing data in the transactions entity projection table to identify user accounts with matching clustering parameter values includes one or more of:
grouping the transactions entity projections in the transactions entity projection table by the selected clustering parameters; and
analyzing the values of the selected clustering parameters for each of the transactions entity projections in the transactions entity projection table to identify transactions entity projections that have matching clustering parameter values.

15. The method of claim 14 , wherein two transactions entity projections are considered to have matching clustering parameter values when the value of each of the clustering parameters for a first of the two transactions entity projections is equal to the value of each of the corresponding clustering parameters for a second of the two transactions entity projections.

16. The method of claim 1 , wherein two transactions entity

Assignees

• Intuit Inc

Inventors

• Rabbani Tarek
• Nene Kishore
• Misra Siddhartha
• Bernal Don Emmanuel

Classifications

• G06F16/215 Primary

  Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors · CPC title

• G06Q40/02 Primary

  Banking, e.g. interest calculation or account maintenance (credit or loans G06Q40/03) · CPC title

• G06F18/2323

  based on graph theory, e.g. minimum spanning trees [MST] or graph cuts · CPC title

• G06F18/22

  Matching criteria, e.g. proximity measures · CPC title

• H04L67/306

  User profiles · CPC title