Phone usage pattern as credit card fraud detection trigger

• US 8,386,386 B1
• Filed: 02/10/2012
• Issued: 02/26/2013
• Est. Priority Date: 01/05/2009
• Status: Active Grant

• Current Assignee: T-Mobile Innovations LLC (Deutsche Telekom AG)
• Original Assignee: Sprint Communications Company LP (Deutsche Telekom AG)
• Inventors: Zhu, Kevin
• Primary Examiner(s): Norman, Samica L
• Application Number:
  US13/371,072
• Time in Patent Office: 382 Days
• Field of Search: 705/44, 705/16, 455/406, 455/407, 379/111, 379/112.01
• US Class Current: 705/44
• CPC Class Codes: G06Q 20/326 Payment applications installed on the mobile devices
• CPC Class Codes: G06Q 20/4016 involving fraud or risk level assessment in transaction processing
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof

Abstract

A credit card fraud reduction system is disclosed. The system comprises a computer system and an application. The application, when executed on the computer system, applies increased credit card fraud prevention procedures to use of an electronic credit card application in a mobile electronic device, based on a changed communication usage pattern of the mobile electronic device.

Claims

1. A credit card fraud reduction system, comprising:

a computer system; and

an application that, when executed on the computer system, applies increased credit card fraud prevention procedures to use of an electronic credit card application in a mobile electronic device at the time of or prior to a payment transaction at a point-of-sale terminal in response to a changed communication usage pattern of the mobile electronic device.

2. The system of claim 1, wherein the mobile electronic device is one of a mobile phone, a personal digital assistant, a media player, a laptop computer, and a tablet computer.

3. The system of claim 1, wherein the usage pattern comprises a pattern of called phone numbers and browsed universal reference locators (URLs).

4. The system of claim 3, wherein the pattern of called phone numbers is based on days of the week and times of day the phone numbers are called and the pattern of browsed universal reference locators is based on days of the week and times of day the universal reference locators are browsed.

5. The system of claim 3, wherein the usage pattern further comprises at least one of an average number of voice calls per unit of time, an average length of voice call, an average number of outgoing data packets per unit of time, an average number of incoming data packets per unit of time, and an average length of time the mobile electronic device is out of network coverage.

6. The system of claim 1, wherein the increased credit card fraud prevention procedures comprise requiring the entry of secure information into the mobile electronic device.

7. The system of claim 1, wherein the communication usage pattern is based on analysis of call detail records produced by a mobile phone service provider.

8. A method of reducing credit card fraud, comprising:

determining, by a fraud detection application stored on a non-transitory computer readable medium and executable by a processor, a communication usage pattern of a mobile electronic device, wherein the mobile electronic device contains an electronic credit card application;

identifying, by the fraud detection application, communication from the mobile electronic device that deviates from the communication usage pattern as a trigger event; and

at the time of or prior to a payment transaction at a point-of-sale terminal and in response to the trigger event, increasing authentication procedures to complete the payment transaction using the electronic credit card application on the mobile electronic device.

9. The method of claim 8, wherein the communication usage pattern is at least one of an average number of voice calls per unit of time, an average length of voice call, an average number of outgoing data packets per unit of time, an average number of incoming data packets per unit of time, and an average length of time the mobile electronic device is out of network coverage.

10. The method of claim 9, wherein the trigger event is identified when one of the number of voice calls during a unit of time drops below the average number of voice calls per unit of time, the average length of voice call determined over a pre-defined number of voice calls drops below the average length of voice call, the number of outgoing data packets during a unit of time drops below the average number of outgoing data packets per unit of time, and the number of incoming data packets during a unit of time drops below the average number of incoming data packets per unit of time.

11. The method of claim 9, wherein the trigger event is identified when one of the number of voice calls during a unit of time is above the average number of voice calls per unit of time, an average length of voice call determined over a pre-defined number of voice calls is above the average length of voice call, the number of outgoing data packets during a unit of time is above the average number of outgoing data packets per unit of time, and the number of incoming data packets during a unit of time is above the average number of incoming data packets per unit of time.

12. The method of claim 8, wherein increasing authentication procedures comprises at least one of requiring entry of a personal identification number to complete payment transactions and requiring presentation of photo identification to complete payment transactions.

13. The method claim 8, further including transmitting an authentication request to the mobile electronic device after the trigger event and asynchronously with respect to a payment transaction using the electronic credit card application on the mobile electronic device.

14. A method of discrete identity theft prevention, comprising:

determining, by a fraud detection application stored on a non-transitory computer readable medium and executable by a processor, a usage pattern of a mobile phone, wherein the usage pattern is based on voice communications and data communications, and wherein the mobile phone contains an electronic credit card application;

identifying, by the fraud detection application, a usage pattern deviation from the usage pattern of the mobile phone;

at the time of or prior to a payment transaction at a point-of-sale terminal and in response to the usage pattern deviation, transmitting, by the fraud detection application, an authentication request to the mobile phone; and

at the time of or prior to the payment transaction at the point-of-sale terminal and in response to the authentication request, the mobile phone prompting a user for input of a security code.

15. The method of claim 14, wherein determining the usage pattern of the mobile phone is based at least in part on analysis of call detail records (CDRs).

16. The method of claim 14, further including transmitting a text message to the mobile phone, wherein the text message summarizes the usage pattern deviation.

17. The method of claim 14, further including transmitting an automated voice message to the mobile phone, wherein the automated voice message summarizes the usage pattern deviation.

18. The method of claim 14, wherein the usage pattern deviation comprises at least one of reduced number of calls per unit time, increased number of calls per unit time, reduced call duration, increased call duration, reduced number of data packets per unit time, and increased number of data packets per unit time.

19. The method of claim 14, wherein the usage pattern deviation comprises at least one of voice calls originated from the mobile phone from non-customary locations and data calls originated from the mobile phone from non-customary locations.

20. The method of claim 14, further including disabling the mobile phone and the electronic credit card application when at least one of the incorrect security code and no security code is entered by the user.