Systems and Methods to Identify Payment Accounts Having Business Spending Activities

• US 20120022945A1
• Filed: 07/21/2011
• Published: 01/26/2012
• Est. Priority Date: 07/22/2010
• Status: Active Grant

• Current Assignee: Visa International Service Association (Visa, Inc.)
• Original Assignee: Visa International Service Association (Visa, Inc.)
• Inventors: Falkenborg, Nathan Kona, Wang, Guangyu
• Granted Patent: US 8,554,653 B2
• Time in Patent Office: Days
• US Class Current: 705/14.53
• CPC Class Codes: G06Q 30/0255 based on user history

Abstract

Systems and methods are provided to generate tools to evaluate the probability of an account being actually used by a business rather than an individual. In one aspect, a computing apparatus includes: a data warehouse configured to store transaction data of accounts issued by a plurality of issuers; and at least one processor configured to calculate values of a first plurality of variables for each of the accounts using the transaction data of the accounts issued by the plurality of issuers. The accounts include business accounts and non-business accounts. The at least one processor is further configured to identify a second plurality of variables from the first plurality of variables for a classification model to distinguish, using the values and logistic regression, the business accounts from the non-business accounts.

Claims

1. A computer-implemented method, comprising:

storing, in a computing apparatus, transaction data of accounts issued by a plurality of issuers;

calculating, by the computing apparatus, values of a first plurality of variables for each of the accounts using the transaction data of the accounts issued by the plurality of issuers, the accounts including first accounts that are issued as accounts for individual consumers and second accounts that are issued as accounts for businesses; and

identifying, by the computing apparatus, a second plurality of variables from the first plurality of variables for a predictive model to distinguish, using the values, the first accounts from the second accounts.

2. The method of claim 1, wherein the identifying of the second plurality of variables is based on logistic regression.

3. The method of claim 2, wherein the identifying of the second plurality of variables includes stepwise variable screening.

4. The method of claim 1, wherein at least a portion of the first plurality of variables are based on tax information.

5. The method of claim 1, wherein the transaction data records payment transactions made in the first accounts and the second accounts during a predetermined period of time;

and the method further comprises;

processing, by the computing apparatus, each respective transaction of the payment transactions, each respective transaction including a payment from a respective issuer to a respective acquirer settled via the computing apparatus.

6. The method of claim 5, wherein the predictive model includes a linear combination of the second plurality of variables;

when computed for an account, the linear combination provides a score indicative of a probability of the account being actually used by a business during the predetermined period of time.

7. The method of claim 6, wherein a predicted probability of the account being actually used by a business during the predetermined period of time is a logistic function of the score.

8. The method of claim 7, wherein the second plurality of variables include:

a count of zip codes of merchants involved in transactions in the account;

an average amount of transactions in the account;

a count of transactions in the account each having a transaction amount above a first threshold;

a spending amount of transactions of the account performed over weekends;

a spending percentage of transactions in the account each having a transaction amount below a second threshold; and

a spending percentage of transactions of the account in a predetermined merchant category group.

9. The method of claim 8, wherein the predetermined merchant category group is one of:

business to business, oil/gas, discount store, department store, drug store, supermarket, and health care.

10. The method of claim 7, wherein the second plurality variables include tax statistical data for entities residing in a region where, during the predetermined period of time, most face to face transactions in the account were conducted.

12. The medium of claim 1, wherein the probability of the respective account being actually used for business purposes is a logistic function of the score.

13. The medium of claim 12, wherein the score is a combination of variables evaluated using transaction data recorded for the respective account.

14. The medium of claim 13, wherein at least a portion of the variables are evaluated based on statistical data about tax returns identified via the transaction data.

15. The medium of claim 14, wherein the instructions are further configured to instruct the computing apparatus to determine a geographic region when most of face to face transactions in the respective account occurred;

and the statistical data about tax returns is identified based on the geographic region.

11. A tangible computer-storage medium storing instructions configured to instruct a computing apparatus to:

process payment transactions for a plurality of accounts;

store transaction data recording the payment transactions for the plurality of accounts;

compute a score for each respective account of the accounts based on the transaction data, the score indicative of a probability of the respective account being actually used for business purposes; and

provide the score to an issuer of the respective account to determine whether to provide an offer to a user of the respective account.

16. The medium of claim 11, wherein the instructions are further configured to instruct the computing apparatus to provide an aggregated spending profile of the respective account to the issuer;

and the offer is determined based on the score and the aggregated spending profile.

17. The medium of claim 16, wherein the offer includes one of:

a business account; and

an account feature tailored for business procurement.

18. A computing apparatus, comprising:

a data warehouse configured to store first transaction data recording payment transactions processed for a plurality of accounts;

a memory storing model data derived from second transaction data of accounts issued by a plurality of issuers; and

at least one processor coupled with the memory and the data warehouse and configured to compute a score for each respective account of the plurality of accounts using the first transaction data and the model data, wherein the model data is configured to provide a predicted probability of the respective account being actually used by a business entity as a logistic function of the score.

19. The computing apparatus of claim 18, further comprising:

a transaction handler configured to process the payment transactions and coupled to the data warehouse to record the first transaction data, wherein the transaction handler is further configured to process payment transactions recorded in the second transaction data.

20. The computing apparatus of claim 18, wherein the transaction handler is configured to communicate with issuer processors and acquirer processors to settle the payment transactions recorded in the second transaction data;

and the computing apparatus further comprises a portal coupled with the at least one processor to receive a request from an issuer and provide the score to the issuer if the respective account is issued by the issuer.