SYSTEM AND METHOD FOR SCREENING FOR FRAUD IN COMMERCIAL TRANSACTIONS

• US 20070244782A1
• Filed: 04/12/2007
• Published: 10/18/2007
• Est. Priority Date: 04/12/2006
• Status: Active Grant

• Current Assignee: Marc A. Chimento
• Original Assignee: Marc A. Chimento
• Inventors: CHIMENTO, Marc A.
• Granted Patent: US 7,427,016 B2
• Time in Patent Office: Days
• US Class Current: 705/35
• CPC Class Codes: G06Q 20/00 Payment architectures, schemes or protocols apparatus for performing or posting payment transactions G07F7/08, G07F19/00; electronic cash registers G07G1/12
• CPC Class Codes: G06Q 20/042 characterized in that the payment protocol involves at least one cheque
• CPC Class Codes: G06Q 20/4016 involving fraud or risk level assessment in transaction processing
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G07D 7/0047 using checkcodes, e.g. coded numbers derived from serial number and denomination

Abstract

A method for screening for potential fraud in commercial paper is provided. For example, a method of the invention comprises steps of presenting a check for cashing to a check cashing agent (e.g., a bank teller); scanning or inspecting the check for data; selecting data for analysis; analyzing selected data with a commercial paper fraud detection system (“CPFDS”); and reporting results of the fraud detection system analysis to the check cashing agent. The commercial paper fraud detection system provides a means for predicting if commercial paper is potentially fraudulent. For example, the commercial paper fraud detection system may detect stolen checks, altered checks, and fabricated or counterfeit checks, among other types of fraud. Also provided is a computer program product for detecting fraud in commercial paper.

Claims

1. A computer program product embodied on a computer readable medium and executable by a microprocessor for detecting fraud in commercial paper comprising computer instructions for executing the steps of

scanning commercial paper for data,

wherein said commercial paper has been received by a commercial paper cashing agent;

determining one or more attributes based on said data;

calculating a risk indicator for said commercial paper,

wherein said risk indicator is a mathematical function of said attributes; and

reporting said risk indicator to said commercial paper cashing agent.

2. A commercial paper fraud detection method comprising the steps of

receiving commercial paper by a commercial paper cashing agent;

scanning said commercial paper for data;

determining one or more attributes based on said data;

calculating a risk indicator for said commercial paper,

wherein said risk indicator is a mathematical function of said attributes; and

reporting said risk indicator to said commercial paper cashing agent.

3. The method according to claim 2, wherein said commercial paper cashing agent is a bank holding an account against which said commercial paper is drawn and said commercial paper is received with a contemporaneous demand for payment in cash.

4. The method according to claim 3, further comprising a step of either honoring or dishonoring said commercial paper.

5. The method according to claim 2, wherein said commercial paper cashing agent is a bank not holding an account against which said commercial paper is drawn.

6. The method according to claim 2, wherein said commercial paper cashing agent is a merchant and said commercial paper is received in consideration for goods or services.

7. The method of claim 2, further comprising a step of comparing said data with a database.

8. The method of claim 2, further comprising a step of entering said data into a database.

9. The method according to claim 2, wherein the magnitude of said risk indicator is proportional to the risk that said commercial paper is fraudulent.

10. The method according to claim 2, wherein said determining step includes determining three or more attributes, and said risk indicator is the sum of the values of said three or more attributes.

11. The method according to claim 2, wherein said determining step includes determining five or more attributes, and said risk indicator is the sum of the values of said five or more attributes.

12. The method according to claim 2, wherein said determining step includes determining seven or more attributes, and said risk indicator is the sum of the values of said seven or more attributes.

13. The method according to claim 2, wherein said mathematical function is addition.

14. The method according to claim 2, wherein each of said one or more attributes has a value of at least zero.

15. The method according to claim 2, wherein each of said one or more attributes has a value of equal to or less than about 100%.

16. The method of claim 2, wherein said commercial paper is a check and said data are selected from the group consisting of the identity of the drawer, the identity of the drawee, the check number, the issue date, the payment amount, the account number, the account type, and the date, time, and location of receiving said check.

17. The method according to claim 16, wherein said one or more attributes comprise a known/unknown account number attribute, wherein said known/unknown account number attribute has a value ofwhen said account number is unknown to said commercial paper cashing agent, orwhen said account number is known to said commercial paper cashing agent.

18. The method according to claim 16, wherein said one or more attributes comprise a duplicate check number attribute, wherein said duplicate check number attribute has a value ofwhen said check number is the same as a check number of a check previously paid for said account number, orwhen said check number is unique with respect to checks previously paid for said account number.

19. The method according to claim 16, wherein said one or more attributes comprise an expected check number attribute, wherein said expected check number attribute has a value of

from about 0% to about 100%, said value being proportional to the magnitude of the difference between said check number and a calculated prediction of the expected next check number for said account number.

20. The method according to claim 16, wherein said one or more attributes comprise an expected minimum check number attribute, wherein said expected minimum check number attribute has a value of

from about 0% to about 100% when said check number is below a calculated prediction of the expected minimum check number for said account number, said value being proportional to the magnitude of the difference between said check number and said calculated prediction of the expected minimum check number, or

when said check number is above a calculated prediction of the expected minimum check number for said account number.

21. The method according to claim 16, wherein said one or more attributes comprise a location activity attribute, wherein said location activity attribute has a value of

from about 0% to about 100%, said value being proportional to the number of checks or the payment amounts thereof previously paid for said account number at different locations of said commercial paper cashing agent.

22. The method according to claim 21, wherein said checks are paid on the same day.

23. The method according to claim 16, wherein said one or more attributes comprise an historical activity attribute, wherein said historical activity attribute has a value of

from about 0% to about 100%, said value being proportional to the magnitude of the difference between the payment amount of said check and the average or total payment amount of previously paid checks for said account number during a preceding time period.

24. The method according to claim 23, wherein said historical activity attribute is an average annual activity attribute, wherein said average annual activity attribute has a value of

from about 0% to about 100%, said value being proportional to the magnitude of the difference between the payment amount of said check and the average payment amount of previously paid checks for said account number during one or more preceding years or one or more preceding years to date.

25. The method according to claim 23, wherein said historical activity attribute is a total annual activity attribute, wherein said total annual activity attribute has a value of

from about 0% to about 100%, said value being proportional to the magnitude of the difference between the payment amount of said check and the total payment amount of previously paid checks for said account number during one or more preceding years or one or more preceding years to date.

26. The method according to claim 23, wherein said historical activity attribute is an average quarterly activity attribute, wherein said average quarterly activity attribute has a value of

from about 0% to about 100%, said value being proportional to the magnitude of the difference between the payment amount of said check and the average payment amount of previously paid checks for said account number during one or more preceding quarters or one or more preceding quarters to date.

27. The method according to claim 23, wherein said historical activity attribute is a total quarterly activity attribute, wherein said total quarterly activity attribute has a value of

from about 0% to about 100%, said value being proportional to the magnitude of the difference between the payment amount of said check and the total payment amount of previously paid checks for said account number during one or more preceding quarters or one or more preceding quarters to date.

28. The method according to claim 23, wherein said historical activity attribute is an average monthly activity attribute, wherein said average monthly activity attribute has a value of

from about 0% to about 100%, said value being proportional to the magnitude of the difference between the payment amount of said check and the average payment amount of previously paid checks for said account number during one or more preceding months or one or more preceding months to date.

29. The method according to claim 23, wherein said historical activity attribute is a total monthly activity attribute, wherein said total monthly activity attribute has a value of

from about 0% to about 100%, said value being proportional to the magnitude of the difference between the payment amount of said check and the total payment amount of previously paid checks for said account number during one or more preceding months or one or more preceding months to date.

30. The method according to claim 23, wherein said historical activity attribute is an average biweekly activity attribute, wherein said average biweekly activity attribute has a value of

from about 0% to about 100%, said value being proportional to the magnitude of the difference between the payment amount of said check and the average payment amount of previously paid checks for said account number during one or more preceding biweeks or one or more preceding biweeks to date.

31. The method according to claim 23, wherein said historical activity attribute is a total biweekly activity attribute, wherein said total biweekly activity attribute has a value of

from about 0% to about 100%, said value being proportional to the magnitude of the difference between the payment amount of said check and the total payment amount of previously paid checks for said account number during one or more preceding biweeks or one or more preceding biweeks to date.

32. The method according to claim 23, wherein said historical activity attribute is an average weekly activity attribute, wherein said average weekly activity attribute has a value of

from about 0% to about 100%, said value being proportional to the magnitude of the difference between the payment amount of said check and the average payment amount of previously paid checks for said account number during one or more preceding weeks or one or more preceding weeks to date.

33. The method according to claim 23, wherein said historical activity attribute is a total weekly activity attribute, wherein said total weekly activity attribute has a value of

from about 0% to about 100%, said value being proportional to the magnitude of the difference between the payment amount of said check and the total payment amount of previously paid checks for said account number during one or more preceding weeks or one or more preceding weeks to date.

34. The method according to claim 16, wherein said one or more attributes comprise a payment amount limit attribute, wherein said payment amount limit attribute has a value ofwhen the payment amount is equal to or exceeds a predetermined maximum payment limit, orwhen the payment amount less than a predetermined maximum payment limit.

35. The method according to claim 16, wherein said one or more attributes comprise a foreign account attribute, wherein said foreign account attribute has a value of

greater than about 0% when the bank holding the account against which said check is drawn is foreign to said commercial paper cashing agent, or

when the bank holding the account against which said check is drawn is not foreign to said commercial paper cashing agent.

36. The method according to claim 35, wherein said foreign account attribute has a value of

greater than about 0% when the bank holding the account against which said check is drawn is out-of-state with respect to said commercial paper cashing agent, or

when the bank holding the account against which said check is drawn is not out-of-state with respect to said commercial paper cashing agent.