TABLE OF CONTENTS Credit-card fraud detection is an extremely difficult problem to solve. Several factors compound the difficulty of this criminal pattern recognition problem. First of all, the data provided in an authorization is extremely limited, such as the amount, location, and perhaps type of product or service being purchased. Second, the patterns of fraudulent use are very diverse. A person can use a credit card at millions of different places and thousands of Web sites, making it extremely difficult to match a pattern. Third, a thief can be using a credit-card number concurrently with an authorized user, making the pattern detection more challenging. A fraud detection model must determine a way to classify transactions made by the authorized party and those made by a non-authorized party. Finally, there is the issue of time and the anonymity of the thief. If he or she can get away with charging a few hundred dollars in a few days on a stolen card number, chances are the thief will never be tracked down. Therefore, fraud detection has to be done in real-time.
At a Web site, real-time fraud detection has to be done right at the virtual checkout counter, when the e-commerce site sends the information to Visa, which can be through several channels, and then as it arrives at the bank that issued the card. Before the bank sends an authorization back to the merchant through Visa, it will run it through a real time detection system. These fraud...
