Fraud risk advisor

• US 20060287902A1
• Filed: 08/24/2006
• Published: 12/21/2006
• Est. Priority Date: 09/17/2004
• Status: Active Grant

• Current Assignee: David Helsper, Dennis Maicon
• Original Assignee: David Helsper, Dennis Maicon
• Inventors: Helsper, David, Maicon, Dennis
• Granted Patent: US 7,438,226 B2
• Time in Patent Office: Days
• US Class Current: 705/7
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03
• CPC Class Codes: G06Q 50/265 Personal security, identity or safety

Abstract

A fraudulent business transaction application (FBTA) is provided for monitoring application based fraud. When a consumer supplies account access information in order to carry out on Internet business transaction, the FBTA uses an online fraud mitigation engine to detect phishing intrusions and identity theft. Methods are also provided for calculating travel velocity and transaction frequency, which are useful for determining a fraudulent transaction.

Claims

1-42. -42. (canceled)

43. A method for determining if one or more online transactions are fraudulent, comprising the steps of:

a. computing a transaction frequency with which the one or more transactions are attempted or executed from an IP address within a predetermined period of time;

b. determining the host type associated with the IP address; and

c. executing a function to determine if the one or more transactions are fraudulent, the function having as its input at least the transaction frequency and the host type.

44. The method of claim 43, wherein host type is network end point, network proxy, or network firewall.

45. The method of claim 44, wherein the function generates a risk score and the one or more transactions are determined to be fraudulent when the risk score exceeds a threshold level.

46. The method of claim 45, wherein the function compares the transaction frequency to the host type in order to optimize the risk score.

47. The method of claim 46, wherein for a predetermined transaction frequency, the function generates a relatively higher risk score when the host type is a network end point then when the host type is a network proxy or a network firewall.