Method and system for duplicate detection

• US 9,092,447 B1
• Filed: 03/08/2013
• Issued: 07/28/2015
• Est. Priority Date: 10/20/2008
• 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: Anderson, Milton M., Scriven, Dieter
• Primary Examiner(s): Bitar, Nancy
• Application Number:
  US13/790,827
• Time in Patent Office: 872 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: G06F 16/1748 De-duplication implemented within the file system, e.g. based on file segments de-duplication techniques in storage systems for the management of data blocks G06F3/0641
• CPC Class Codes: G06Q 20/042 characterized in that the payment protocol involves at least one cheque
• CPC Class Codes: G06Q 20/382 insuring higher security of transaction
• CPC Class Codes: G06Q 20/3827 Use of message hashing
• CPC Class Codes: G06Q 20/4016 involving fraud or risk level assessment in transaction processing
• CPC Class Codes: G06Q 30/0185 Product, service or business identity fraud
• CPC Class Codes: G06Q 40/12 Accounting
• CPC Class Codes: G06V 30/2253 Recognition of characters printed with magnetic ink G06V30/2247 takes precedence
• CPC Class Codes: G06V 30/418 Document matching, e.g. of document images
• CPC Class Codes: G07F 7/04 by paper currency
• 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: G07F 7/125 Offline card verification

Abstract

A system and method for detecting duplicates during processing. The duplicate detection may be performed by a financial institution, such as a bank. The method may be implemented on a computer based system. The duplicate detection method may be automated. The method may be applied initially to incoming electronic data files prior to further processing of the electronic data to prevent processing of duplicate items. The system and method may use a function, such as a hash function, to perform the duplicate detection. Other functions, such as a Bloom filter which may use multiple hash functions, may be used to perform the duplicate detection.

Claims

1. A system for detecting duplicate transactions, comprising:

at least one processor;

a memory comprising computer-readable instructions which when executed by the processor cause the processor to perform the steps comprising;

receiving electronic data that comprises accounting data associated with one or more transactions;

processing the electronic data to extract the accounting data;

creating a character string from a subset of the accounting data for each of the one or more transactions;

applying a Bloom filter using multiple hash functions to the character string;

determining that a transaction is a potential suspected duplicate if each bit value read is equal to a first value;

determining that the transaction is not a suspected duplicate if at least one bit value is not equal to the first value;

outputting a listing of each potential suspected duplicate; and

performing additional processing on each potential suspected duplicate to determine if the potential suspected duplicate is a true suspected duplicate.

2. The system of claim 1, further comprising:

comparing the electronic data to an exclusion table; and

removing the electronic data from further processing upon transaction data appearing on the exclusion table.

3. The system of claim 1, further comprising:

allowing a user to interact with the system through an interface.

4. The system of claim 3, wherein the interface allows a user to review the listing of suspected duplicates.

5. The system of claim 1, wherein the electronic data is in a format from which the accounting data can be extracted.

6. The system of claim 1, wherein the accounting data comprises electronic data elements.

7. The system of claim 4, wherein the user queues one or more of the true suspected duplicates for fraud analysis.

8. The system of claim 1, wherein the determination of suspected duplicates is performed against transaction data for a predetermined time period.

9. The system of claim 1, wherein the Bloom filter is part of a Bloom filter service.

10. The system of claim 9, further comprising:

starting the Bloom filter service upon receipt of the electronic data.

11. The system of claim 10, further comprising:

stopping the Bloom filter service upon completion of determining if each transaction is a suspected duplicate.

12. The system of claim 1, wherein the one or more transactions comprise bankcard transactions.

13. The system of claim 12, wherein the bankcard transactions comprise credit or debit transactions.

14. The system of claim 12, wherein the electronic data comprises:

card number, transaction amount, card type, currency code, and merchant name.

15. The system of claim 1, wherein the one or more transactions comprise ACH payments.

16. The system of claim 15, wherein the electronic data comprises:

bank account number, bank account type, bank routing number, transaction amount, payee name, and effective date.

17. The system of claim 1, wherein the one or more transactions comprise wire transfers.

18. The system of claim 17, wherein the electronic data comprises:

receiver bank routing number, type code, sender bank routing number, sender bank reference number, and transaction amount.

37. The system of claim 1, wherein the multiple hash functions comprise four hash functions.

19. A method for detecting duplicate transactions, comprising:

receiving electronic data that comprises accounting data associated with one or more transactions;

processing, by at least one computer processor, the electronic data to extract the accounting data;

creating, by the at least one computer processor, a character string from a subset of the accounting data for each of the one or more transactions;

applying a Bloom filter using multiple hash functions to the character string;

determining that a transaction is a potential suspected duplicate if each bit value read is equal to a first value;

determining that the transaction is not a suspected duplicate if at least one bit value is not equal to the first value;

outputting a listing of each potential suspected duplicate; and

performing additional processing on each potential suspected duplicate to determine if the potential suspected duplicate is a true suspected duplicate.

20. The method of claim 19, further comprising:

comparing the electronic data to an exclusion table; and

removing the electronic data from further processing upon transaction data appearing on the exclusion table.

21. The method of claim 19, further comprising:

allowing a user to interact with the system through an interface.

22. The method of claim 21, wherein the interface allows a user to review the listing of suspected duplicates.

23. The method of claim 19, wherein the electronic data is in a format from which the accounting data can be extracted.

24. The method of claim 19, wherein the accounting data comprises electronic data elements.

25. The method of claim 22, wherein the user queues one or more of the true suspected duplicates for fraud analysis.

26. The method of claim 19, wherein the determination of suspected duplicates is performed against transaction data for a predetermined time period.

27. The method of claim 19, wherein the Bloom filter is part of a Bloom filter service.

28. The method of claim 27, further comprising:

starting the Bloom filter service upon receipt of the electronic data.

29. The method of claim 28, further comprising:

stopping the Bloom filter service upon completion of determining if each transaction is a suspected duplicate.

30. The method of claim 19, wherein the one or more transactions comprise bankcard transactions.

31. The method of claim 30, wherein the bankcard transactions comprise credit or debit transactions.

32. The method of claim 30, wherein the electronic data comprises:

card number, transaction amount, card type, currency code, and merchant name.

33. The method of claim 19, wherein the one or more transactions comprise ACH payments.

34. The method of claim 33, wherein the electronic data comprises:

bank account number, bank account type, bank routing number, transaction amount, payee name, and effective date.

35. The method of claim 19, wherein the one or more transactions comprise wire transfers.

36. The method of claim 35, wherein the electronic data comprises:

receiver bank routing number, type code, sender bank routing number, sender bank reference number, and transaction amount.

38. The method of claim 19, wherein the multiple hash functions comprise four hash functions.