SYSTEMS AND METHODS FOR DETERMINING FRAUDULENT TRANSACTIONS USING DIGITAL WALLET DATA

• US 20160078443A1
• Filed: 05/22/2015
• Published: 03/17/2016
• Est. Priority Date: 09/16/2014
• Status: Active Grant

• Current Assignee: Mastercard International Incorporated (MasterCard Incorporated)
• Original Assignee: Mastercard International Incorporated (MasterCard Incorporated)
• Inventors: Tomasofsky, Christian P., Hubbard, Steve E., da Silva, Luis Felipe de Almeida Ferreira
• Granted Patent: US 10,657,521 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 21/34 involving the use of external additional devices, e.g. dongles or smart cards
• CPC Class Codes: G06F 2221/2103 Challenge-response
• CPC Class Codes: G06Q 10/0635 Risk analysis of enterprise or organisation activities
• CPC Class Codes: G06Q 20/36 using electronic wallets or electronic money safes
• CPC Class Codes: G06Q 20/363 with the personal data of a user
• CPC Class Codes: G06Q 20/3674 involving authentication
• CPC Class Codes: G06Q 20/4014 Identity check for transactions
• CPC Class Codes: G06Q 20/4016 involving fraud or risk level assessment in transaction processing
• CPC Class Codes: G06Q 20/405 Establishing or using transaction specific rules
• CPC Class Codes: G06Q 20/407 Cancellation of a transaction
• CPC Class Codes: G06Q 20/409 Device specific authentication in transaction processing
• CPC Class Codes: G06Q 30/0229 Multi-merchant loyalty card systems

Abstract

A computing device for risk-based analysis of a payment card transaction is provided herein. The computing device includes a processor communicatively coupled to a memory. The computing device is programmed to receive a request for authentication of the payment card transaction. The payment card transaction includes a suspect consumer presenting a payment card from a digital wallet of a privileged cardholder. The computing device is also programmed to identify fraud feature data from the digital wallet. The computing device is further programmed to compute a fraud score for the payment card transaction based at least in part on the fraud feature data. The computing device is still further programmed to provide the fraud score for use during authentication of the suspect consumer.

Claims

1. A computing device for risk-based analysis of a payment card transaction, said computing device comprising a processor communicatively coupled to a memory, said computing device programmed to:

receive a request for authentication of the payment card transaction, wherein the payment card transaction includes a suspect consumer presenting a payment card from a digital wallet of a privileged cardholder;

identify fraud feature data from the digital wallet;

compute a fraud score for the payment card transaction based at least in part on the fraud feature data; and

provide the fraud score for use during authentication of the suspect consumer.

2. The computing device of claim 1, wherein the fraud feature data from the digital wallet includes historical authentication data associated with one or more prior access instances of the privileged cardholder authenticating into the digital wallet, wherein said computing device is further programmed to compute the fraud score based at least in part on comparing a current authentication method to the historical authentication data.

3. The computing device of claim 1, wherein the fraud feature data from the digital wallet includes personal data associated with past transactions involving the digital wallet, wherein said computing device is further programmed to compute the fraud score based at least in part on comparing current transaction data with the personal data.

4. The computing device of claim 1, wherein the fraud feature data from the digital wallet includes device data associated with past transactions involving the digital wallet, wherein said computing device is further programmed to compute the fraud score based at least in part on comparing a device used in the payment transaction to the device data.

5. The computing device of claim 1, wherein the fraud feature data from the digital wallet includes loyalty account data, wherein said computing device is further programmed to compute the fraud score based at least in part on comparing the loyalty account data to current loyalty account data of the payment card transaction.

6. The computing device of claim 1, wherein said computing device is further programmed to:

compute a digital wallet score based at least in part on the fraud feature data;

identify a device score for the payment card transaction; and

compute the fraud score based at least in part on both the digital wallet score and the device score.

7. The computing device of claim 1, wherein said computing device is further programmed to:

receive a scoring configuration profile; and

compute the fraud score based at least in part on the scoring configuration profile and the payment card transaction.

8. A computer-based method for risk-based analysis of a payment card transaction, the method implemented using a computer device including a processor and a memory, said method comprising:

receiving a request for authentication of the payment card transaction, wherein the payment card transaction includes a suspect consumer presenting a payment card from a digital wallet of a privileged cardholder;

identifying fraud feature data from the digital wallet;

computing a fraud score for the payment card transaction based at least in part on the fraud feature data; and

providing the fraud score for use during authentication of the suspect consumer.

9. The method of claim 8, wherein the fraud feature data from the digital wallet includes historical authentication data associated with one or more prior access instances of the privileged cardholder authenticating into the digital wallet, wherein computing a fraud score further includes comparing a current authentication method to the historical authentication data.

10. The method of claim 8, wherein the fraud feature data from the digital wallet includes personal data associated with past transactions involving the digital wallet, wherein computing a fraud score further includes comparing current transaction data with the personal data.

11. The method of claim 8, wherein the fraud feature data from the digital wallet includes device data associated with past transactions involving the digital wallet, wherein computing a fraud score further includes comparing a device used in the payment transaction to the device data.

12. The method of claim 8, wherein the fraud feature data from the digital wallet includes loyalty account data, wherein computing a fraud score further includes comparing the loyalty account data to current loyalty account data of the payment card transaction.

13. The method of claim 8, wherein computing a fraud score further includes:

computing a digital wallet score based at least in part on the fraud feature data;

identifying a device score for the payment card transaction; and

computing the fraud score based at least in part on both the digital wallet score and the device score.

14. The method of claim 8 further comprising receiving a scoring configuration profile, wherein computing the fraud score further includes computing the fraud score based at least in part on the scoring configuration profile and the payment card transaction.

15. At least one non-transitory computer-readable storage media having computer-executable instructions embodied thereon, wherein when executed by at least one processor, the computer-executable instructions cause the processor to:

receive a request for authentication of a payment card transaction, wherein the payment card transaction includes a suspect consumer presenting a payment card from a digital wallet of a privileged cardholder;

identify fraud feature data from the digital wallet;

compute a fraud score for the payment card transaction based at least in part on the fraud feature data; and

provide the fraud score for use during authentication of the suspect consumer.

16. The computer-readable storage media of claim 15, wherein the fraud feature data from the digital wallet includes historical authentication data associated with one or more prior access instances of the privileged cardholder authenticating into the digital wallet, wherein the computer-executable instructions further cause the processor to compute the fraud score based at least in part on comparing a current authentication method to the historical authentication data.

17. The computer-readable storage media of claim 15, wherein the fraud feature data from the digital wallet includes personal data associated with past transactions involving the digital wallet, wherein the computer-executable instructions further cause the processor to compute the fraud score based at least in part on comparing current transaction data with the personal data.

18. The computer-readable storage media of claim 15, wherein the fraud feature data from the digital wallet includes device data associated with past transactions involving the digital wallet, wherein the computer-executable instructions further cause the processor to compute the fraud score based at least in part on comparing a device used in the payment transaction to the device data.

19. The computer-readable storage media of claim 15, wherein the fraud feature data from the digital wallet includes loyalty account data, wherein the computer-executable instructions further cause the processor to compute the fraud score based at least in part on comparing the loyalty account data to current loyalty account data of the payment card transaction.

20. The computer-readable storage media of claim 15, wherein the computer-executable instructions further cause the processor to:

compute a digital wallet score based at least in part on the fraud feature data;

identify a device score for the payment card transaction; and

compute the fraud score based at least in part on both the digital wallet score and the device score.

21. The computer-readable storage media of claim 15, wherein the computer-executable instructions further cause the processor to:

receive a scoring configuration profile; and

compute the fraud score based at least in part on the scoring configuration profile and the payment card transaction.