Mass compromise/point of compromise analytic detection and compromised card portfolio management system

• US 20070061259A1
• Filed: 06/26/2006
• Published: 03/15/2007
• Est. Priority Date: 06/24/2005
• Status: Active Grant

• Current Assignee: Fair Isaac Corporation
• Original Assignee: Fair Isaac Corporation
• Inventors: Wu, Steven, Wang, Liang, Sun, Li, Zoldi, Scott
• Granted Patent: US 7,761,379 B2
• Time in Patent Office: Days
• US Class Current: 705/44
• CPC Class Codes: G06Q 20/04 Payment circuits
• CPC Class Codes: G06Q 20/10 specially adapted for electronic funds transfer [EFT] systems; specially adapted for home banking systems
• CPC Class Codes: G06Q 20/40 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 20/4016 involving fraud or risk level assessment in transaction processing
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions
• 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 40/06 Asset management; Financial planning or analysis

Abstract

A system and method for managing mass compromise of financial transaction devices is disclosed. A method includes maintaining a summary of a transaction history for a financial transaction device, and forming a device history profile based on the transaction history, the device history profile including predictive variables indicative of fraud associated with the financial transaction device. A method further includes generating a fraud score based on the predictive variables, the fraud score representing a likelihood that the financial transaction device is compromised will be used fraudulently.

Claims

1. A computer-implemented method comprising:

maintaining a summary of a transaction history for a financial transaction device;

forming a device history profile based on the transaction history, the device history profile including predictive variables indicative of fraud associated with the financial transaction device; and

generating a fraud score based on the predictive variables, the fraud score representing a likelihood that the financial transaction device is compromised and will be used fraudulently.

2. A method in accordance with claim 1, further comprising summarizing activity of the financial transaction device using the predictive variables to determine whether the financial transaction device is compromised and will be used fraudulently.

3. A method in accordance with claim 1, further comprising generating a compromise portfolio profile having compromise cluster variables indicative of a mass compromise of a plurality of financial transaction devices.

4. A method in accordance with claim 3, further comprising combining financial transaction device predictive variables with the compromise cluster variables to determine whether the financial transaction device is associated with the mass compromise and will be used fraudulently.

5. A method in accordance with claim 1, further comprising forming a compromise device global profile that includes transaction arrays that maintain a history of time and location information where the financial transaction device was used.

6. A method in accordance with claim 5, wherein the compromise device global profile includes one or more links to a compromise device global profile index.

7. A method in accordance with claim 6, wherein the compromise device global profile index includes a key to the compromise device global profile.

8. A method in accordance with claim 1, further comprising generating a merchant profile associated with a merchant, the merchant profile including merchant fraud detection variables indicative of fraud and device testing associated with the merchant.

9. A method in accordance with claim 8, wherein the merchant profile further includes a merchant identifier associated with the merchant, and a compromise merchant global profile index key to a compromise merchant global profile.

10. A method in accordance with claim 9, wherein the compromise merchant global profile includes an array indexed by time, the array including a number of financial transaction devices, a number of fraudulent financial transaction devices, and a number of cases of counterfeit and MOTO fraud devices associated with the merchant.

11. A method in accordance with claim 10, further comprising detecting, using the compromise merchant global profile, patterns associated with the number of financial transaction devices that previously transacted at the merchant based on pre-fraud patterns that are anomalous and indicative of potential compromise.

12. A computer-implemented method comprising:

forming a device profile associated with a financial transaction device and based on a transaction history, the device profile including predictive variables that are indicative of a fraud;

generating a fraud score based on the predictive variables, the fraud score representing a likelihood that the financial transaction device is compromised; and

based on predictive variables, determining whether the financial transaction device will be used fraudulently in the near future.

13. A method in accordance with claim 12, wherein the device fraud score further includes compromise cluster variables that are indicative of a mass compromise of a plurality of financial transaction devices.

14. A method in accordance with claim 13, further comprising using predictive variables of the financial transaction device profile with the compromise cluster variables to determine whether the transaction device is associated with the mass compromise and will be used fraudulently.

15. A method in accordance with claim 12, further comprising forming a compromise device global profile that includes transaction arrays that maintain a history of date/times and merchants where the financial transaction device transacted.

16. A method in accordance with claim 15, wherein the device profile includes one or more links to a primary compromise device global profile index

17. A method in accordance with claim 16, wherein the compromise device global profile index includes a key to the compromise card global profile.

22. A system in accordance with claim 17, further comprising a device holder profile that includes compromise cluster variables indicative of a mass compromise of a plurality of financial transaction devices.

23. A method in accordance with claim 22, wherein the compromise merchant global profile is used to detect patterns in the pre-fraud pattern associated with devices that previously transacted at the merchant, based on pre-fraud patterns that are anomalous and indicative of potential compromise.

18. A system for managing compromise of financial transaction devices, the system comprising:

a transaction history for a financial transaction device;

a compromise device global profile associated with the transaction history, the device global profile including predictive variables indicative of fraud; and

a fraud score based on the predictive variables, the fraud score representing a likelihood the financial transaction device is compromised and will be used fraudulently.

19. A system in accordance with claim 18, wherein the compromise device global profile includes transaction arrays that maintain a history of time and location information where the financial transaction device was used.

20. A system in accordance with claim 19, further comprising a merchant profile, the merchant profile including merchant fraud detection variables indicative of fraud and compromise device testing associated with the merchant.

21. A system in accordance with claim 20, wherein the merchant profile further includes a merchant identifier associated with the first merchant, and a primary compromise merchant global profile index key to a compromise merchant global profile.