System and method for screening for fraud in commercial transactions

• US 7,427,016 B2
• Filed: 04/12/2007
• Issued: 09/23/2008
• Est. Priority Date: 04/12/2006
• Status: Expired due to Fees

• Current Assignee: Marc A. Chimento
• Original Assignee: Marc A. Chimento
• Inventors: Chimento, Marc A.
• Primary Examiner(s): Hess; Daniel A
• Application Number:
  US11/734,316
• Publication Number:
  US 20070244782A1
• Time in Patent Office: 530 Days
• Field of Search: 235/376, 235/380, 235/379, 705/35, 705/45
• US Class Current: 235/376
• 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 commercial paper fraud detection method comprising the steps of:

receiving commercial paper by a commercial paper cashing agent;

wherein said commercial paper is a check;

scanning said commercial paper for data;

wherein 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;

determining one or more attributes based on said data;

wherein said one or more attributes comprise a known/unknown account number attribute and wherein said known/unknown account number attribute has a value of 100% when said account number is unknown to said commercial paper cashing agent, or 0% when said account number is known to said commercial paper cashing agent;

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. The system according to claim 1, 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.

3. The system according to claim 1, wherein said commercial paper cashing agent is a bank not holding an account against which said commercial paper is drawn.

4. The system according to claim 1, wherein said commercial paper cashing agent is a merchant and said commercial paper is received in consideration for goods or services.

5. The system according to claim 1, wherein the magnitude of said risk indicator is proportional to the risk that said commercial paper is fraudulent.

6. The system according to claim 1, wherein said mathematical function is addition.

7. The method according to claim 1, wherein said one or more attributes further comprise a duplicate check number attribute, wherein said duplicate check number attribute has a value of 100% when said check number is the same as a check number of a check previously paid for said account number, or 0% when said check number is unique with respect to checks previously paid for said account number.

8. The method according to claim 1, wherein said one or more attributes further 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.

9. The method according to claim 1, wherein said one or more attributes further 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 0% when said check number is above a calculated prediction of the expected minimum check number for said account number.

10. The method according to claim 1, wherein said one or more attributes further 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.

11. The method according to claim 10, wherein said checks are paid on the same day.

12. The method according to claim 1, wherein said one or more attributes further comprise a payment amount limit attribute, wherein said payment amount limit attribute has a value of 100% when the payment amount is equal to or exceeds a predetermined maximum payment limit, or 0% when the payment amount less than a predetermined maximum payment limit.

13. The method according to claim 1, wherein said one or more attributes further 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 0% when the bank holding the account against which said check is drawn is not foreign to said commercial paper cashing agent.

14. The method according to claim 13, 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 0% 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.

15. A commercial paper fraud detection method comprising the steps of:

receiving commercial paper by a commercial paper cashing agent;

wherein said commercial paper is a check;

scanning said commercial paper for data;

wherein 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;

determining one or more attributes based on said data;

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;

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.

16. The method according to claim 15, 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.

17. The method according to claim 15, 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.

18. The method according to claim 15, 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.

19. The method according to claim 15, 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.

20. The method according to claim 15, 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.

21. The method according to claim 15, 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.

22. The method according to claim 15, 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.

23. The method according to claim 15, 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.

24. The method according to claim 15, 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.

25. The method according to claim 15, 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.