Method and system for automating fraud authorization strategies

• US 8,032,438 B1
• Filed: 04/20/2010
• Issued: 10/04/2011
• Est. Priority Date: 03/12/2008
• Status: Active Grant

• Current Assignee: JP Morgan Chase Bank, N.A. (JP Morgan Chase & Co)
• Original Assignee: JP Morgan Chase Bank, N.A. (JP Morgan Chase & Co)
• Inventors: Barton, Thomas C., Paulson, Harold Jr.
• Primary Examiner(s): Dass; Harish T
• Application Number:
  US12/763,668
• Time in Patent Office: 532 Days
• Field of Search: 705/44, 705/10, 705/18, 705 35- 41, 705/7.31, 235/380, 283/66.1, 340/425.5
• US Class Current: 705/35
• CPC Class Codes: G06Q 20/10 specially adapted for electronic funds transfer [EFT] systems; specially adapted for home banking systems
• CPC Class Codes: G06Q 20/102 Bill distribution or payments
• CPC Class Codes: G06Q 20/105 involving programming of a portable memory device, e.g. IC cards, "electronic purses"
• CPC Class Codes: G06Q 20/40 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 Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange

Abstract

According to an embodiment of the present invention, a computer implemented method and system for automatically implementing a fraud strategy may involve identifying transaction data related to a customer transaction based on a payment instrument; automatically identifying a pattern based on one or more factors associated with a customer spending profile; identifying a potential fraud situation based on the identified pattern and the transaction data; executing an action for the potential fraud situation; and adjusting authorized use of the payment instrument.

Claims

1. A computer implemented method for automatically implementing a fraud strategy, the method comprising the steps of:

using a computer processor;

receiving transaction data related to a customer transaction based on a payment instrument;

retrieving a customer spending profile for the customer from at least one database;

automatically identifying a spending pattern based on one or more factors associated with the customer spending profile;

automatically determining that the customer transaction is a normal transaction based on a consistency between the identified spending pattern and the transaction data; and

approving the customer transaction.

2. The method of claim 1, wherein the one or more factors associated with the customer spending profile comprise one or more of merchant data, customer spending data, customer demographic data, profitability data and delinquency data.

3. The method of claim 1, wherein the determination that the customer transaction is a normal transaction is further based on one or more exclusions for fraud detection.

4. The method of claim 3, wherein the one or more exclusions comprise one or more of customer travel and emergency expenses.

5. The method of claim 1, wherein the determination that the customer transaction is a normal transaction is further based on one or more exceptions.

6. The method of claim 5, wherein the exception is submitted by the customer.

7. The method of claim 1, wherein the determination that the customer transaction is a normal transaction is further based on a current location of the customer relative to the location of the customer transaction.

8. The method of claim 1, further comprising:

updating the customer spending profile based on the customer transaction.

9. The method of claim 1, wherein the payment instrument is at least one of a physical device and an account.

10. A computer implemented method for automatically implementing a fraud strategy, the method comprising the steps of:

using a computer processor;

receiving transaction data related to a customer transaction based on a payment instrument;

retrieving a customer spending profile for the customer from at least one database;

automatically identifying a spending pattern based on one or more factors associated with the customer spending profile;

automatically determining that the customer transaction is a normal transaction based on a consistency between the identified spending pattern and the transaction data; and

updating the customer spending profile based on the customer transaction.

11. The method of claim 10, wherein the one or more factors associated with the customer spending profile comprise one or more of merchant data, customer spending data, customer demographic data, profitability data and delinquency data.

12. The method of claim 10, wherein the determination that the customer transaction is a normal transaction is further based on one or more exclusions for fraud detection.

13. The method of claim 12, wherein the one or more exclusions comprise one or more of customer travel and emergency expenses.

14. The method of claim 10, wherein the determination that the customer transaction is a normal transaction is further based on one or more exceptions.

15. The method of claim 14, wherein the exception is submitted by the customer.

16. The method of claim 10, wherein the determination that the customer transaction is a normal transaction is further based on a current location of the customer relative to the location of the customer transaction.

17. The method of claim 10, further comprising:

updating the customer spending profile based on the customer transaction.

18. A computer implemented system for automatically implementing a fraud strategy, comprising:

at least one computer processor;

at least one computer memory;

a pattern detection module for identifying transaction data related to a customer transaction based on a payment instrument;

automatically identifying a spending pattern based on one or more factors associated with a customer spending profile; and

determining that the customer transaction is a normal transaction based on a consistency between the identified spending pattern and the transaction data; and

an action module for performing at least one of approving the transaction and updating the customer spending profile based on the customer transaction.

19. The system of claim 18, wherein the one or more factors associated with the customer spending profile comprise one or more of merchant data, customer spending data, customer demographic data, profitability data and delinquency data.

20. The system of claim 18, wherein the pattern detection module further determines the customer'"'"'s current location relative to the location of the customer transaction.

21. The system of claim 18, wherein the pattern detection module further determines the customer'"'"'s transaction history compared to the customer transaction.

22. The system of claim 18, wherein the action module further applies one or more exclusions for fraud detection.

23. The system of claim 22, wherein the one or more exclusions comprise one or more of customer travel and emergency expenses.

24. The system of claim 18, wherein the action module further applies one or more exceptions.

25. The system of claim 24, wherein the exception is submitted by the customer.

26. The system of claim 18, wherein the payment instrument is at least one of a physical device and an account.

27. A computer implemented method for automatically implementing a fraud strategy, the method comprising the steps of:

using a computer processor;

receiving transaction data related to a customer transaction based on a payment instrument;

retrieving a customer spending profile for the customer from at least one database;

automatically identifying a spending pattern based on one or more factors associated with the customer spending profile;

automatically determining that the customer transaction is a normal transaction based on a consistency between the identified spending pattern, the transaction data and the application of one or more exclusions for fraud detection and one or more exceptions;

approving the customer transaction; and

updating the customer spending profile based on the customer transaction;

wherein the one or more factors associated with the customer spending profile comprise one or more of merchant data, customer spending data, customer demographic data, profitability data, delinquency data; and

wherein the one or more exclusions comprise one or more of customer travel and emergency expenses; and

wherein the exception is submitted by the customer.