Scoring methodology for purchasing card fraud detection

• US 6,418,436 B1
• Filed: 12/20/1999
• Issued: 07/09/2002
• Est. Priority Date: 12/20/1999
• Status: Expired due to Term

• Current Assignee: First Data Corporation (Fiserv Incorporated)
• Original Assignee: First Data Corporation (Fiserv Incorporated)
• Inventors: Degen, Robert G., Ritter, Duane
• Primary Examiner(s): Popovici, Dov
• Assistant Examiner(s): Mofiz, Apu M
• Application Number:
  US09/467,621
• Time in Patent Office: 932 Days
• Field of Search: 705/1, 705/26, 705/35, 707/1, 707/6, 707/10, 707/2, 707/3, 707/4, 707/5
• US Class Current: 1/1
• CPC Class Codes: G06Q 20/24 Credit schemes, i.e. "pay after"
• CPC Class Codes: G06Q 20/4016 involving fraud or risk level assessment in transaction processing
• CPC Class Codes: G06Q 20/4037 Remote solvency checks
• CPC Class Codes: G07F 7/08 by coded identity card or credit card or other personal identification means without personal verification means G07F7/02
• CPC Class Codes: Y10S 707/99936 Pattern matching access
• CPC Class Codes: Y10S 707/99945 Object-oriented database structure processing

Abstract

A method and system is disclosed for scoring a match between applicant data provided by a client and data stored in a fraud database. The system includes a merchant application having a unique identifier portion, a non-unique identifier portion, and a reference portion, a processor having access to the merchant information for calculating a first match score based on a match occurring in the non-unique identifier portion, a second match score based on a match occurring in the unique identifier portion, and a third match score based on a match occurring in the reference portion, and wherein the processor sums the first, second, and third match scores to arrive at a total match score to determine whether the total match score has exceeded a predefined match score. If the predefined match score is exceed then an alert is sent to the client informing the client that a fraud match with a high degree of reliability has occurred.

Claims

1. A method for determining likelihood of a fraudulent purchasing card traction using a fraud database having fraud data used in known frauds, the method comprising:

providing purchasing card applicant data for a purchasing card transaction, the purchasing card applicant data including a unique identifier portion having at least one unique identifier data element, a non unique identifier portion having at least one non-unique identifier data element, and a reference portion having at least one reference data element;

determining whether any of the purchasing card applicant data matches any of the fraud data used in known frauds of the fraud database;

determining which matched purchasing card applicant data occurs in the unique identifier portion, the non-unique identifier portion, and the reference portion;

determining which at least one unique identifier data element of the unique identifier portion matches any of the fraud data used in known frauds of the fraud database for each matched purchasing card applicant data occurring in the unique identifier portion;

determining which at least one non-unique identifier data element of the non-unique identifier portion matches any of the fraud data used in known frauds of the fraud database for each matched purchasing card applicant data occurring in the non-unique identifier portion;

determining which at least one reference data element of the reference portion matches any of the fraud data used in known frauds of the fraud database for each matched purchasing card applicant data occurring in the reference portion;

calculating a first match score based on each matched at least one unique identifier data element;

calculating a second match score based on each matched at least one non-unique identifier data element;

calculating a total match score by summing the first and second match scores; and

determining likelihood of the purchasing card transaction being fraudulent as a function of the total match score, wherein the purchasing card transaction is determined to be fraudulent when the total match score is greater than a predefined match score.

2. The method of claim 1 wherein the purchasing card applicant data includes personal information included on a merchant application.

3. The method of claim 2 wherein the personal information included on the merchant application is in a pipe delineated format.

4. The method of claim 1 wherein the unique identifier portion includes an applicant name field.

5. The method of claim 1 wherein the non-unique identifier portion includes an applicant address field.

6. The method of claim 1 further comprising assigning a first match score indicative of the purchasing card transaction being fraudulent when at least one of the at least one unique identifier data element of the unique identifier portion identically matches fraud data used in known frauds of the fraud database.

7. The method of claim 1 wherein calculating a fist match score based on each matched at least one unique identifier data element includes assigning a match score to each matched at least one unique identifier data element weighted as a function of the level of matching with fraud data used in known frauds of the fraud database.

8. The method of claim 1 wherein calculating a second match score based on each matched at least one non-unique identifier data element includes assigning a match score to each matched at least one unique identifier data element which is less than the predefined match score.

9. The method of claim 1 further comprising sending an alert to a merchant client involved in the purchasing card transaction when the total match score exceeds the predefined match score.

10. A system for determining likelihood of a fraudulent purchasing card transaction using a fraud database having fraud data used in known frauds, the system comprising:

purchasing card applicant data for a purchasing card transaction, the purchasing card applicant data including a unique identifier portion having at least one unique identifier data element, a non-unique identifier portion having at least one non-unique identifier data element, and a reference portion having at least one reference data element;

a processor operable for determining whether any of the purchasing card applicant data matches any of the fraud data used in known frauds of the fraud database and for determining which matched purchasing card applicant data occurs in the unique identifier portion, the nonunique identifier portion, and the reference portion;

wherein the processor is further operable for determining which at least one unique identifier data element of the unique identifier portion matches any of he fraud data used in known frauds of the fraud database for each matched purchasing card applicant data occurring in the unique identifier portion, determining which at least one non-unique identifier data element of the non-unique identifier portion matches any of the fraud data used in known frauds of the fraud database for each matched purchasing card applicant data occurring in the non-unique identifier portion, and determining which at least one reference data element of the reference portion matches any of the fraud data used in known frauds of the fraud database for each matched purchasing card applicant data occurring in the reference portion;

wherein the processor is further operable for calculating a first match score based on each matched at least one unique identifier data element, calculating a second match score based on each matched at least one non-unique identifier data element, and calculating a total match score by summing the first and second match scores;

wherein the processor is further operable for determining likelihood of the purchasing card transaction being fraudulent as a function of the total match score, wherein the purchasing card transaction is determined to be fraudulent when the total match score is greater than a predefined match score.

11. The system of claim 10 wherein the purchasing card applicant data includes personal information included on a merchant application.

12. The system of claim 11 wherein the personal information included on the merchant application is in a pipe delineated format.

13. The system of claim 10 wherein the unique identifier portion includes an applicant name field.

14. The system of claim 10 wherein the non-unique identifier portion includes an applicant address field.

15. The system of claim 10 wherein the processor assigns a first match score exceeding the predefined match score when the at least one of the at least one unique identifier data element of the unique identifier portion identically matches fraud data used in known frauds of the fraud database.

16. The system of claim 10 wherein the processor calculates a first match score based on each matched at least one unique identifier data element by assigning a match score to each matched at least one unique identifier data element weighted as a function of the level of matching with fraud data used in known frauds of the fraud database.

17. The system of claim 10 wherein the processor calculates a second match score based on each matched at least one non-unique identifier data element by assigning a match score to each matched at least one non-unique identifier data element weighted as a function of the level of matching with fraud data used in known frauds of the fraud database.

18. The system of claim 10 further comprising sending an alert to a merchant client involved in the purchasing card transaction when the total match score exceeds the predefined match score.