A novel and successful credit card fraud detection system Implemented in a Turkish Bank

Abstract

We developed a credit card fraud detection solution for a major bank in Turkey. The study was completed in about three years and the developed system has been in use since February 2013. It had a great impact in the rule based fraud detection process used by the bank. Indeed, while eighty percent of the rules have been eliminated and the number of alerts has been reduced to half, a significant increase in fraud detection has been recorded. As of now the system can catch ninety seven percent of fraud attempts online or, nearly online. The study is interesting in both the formulation of the problem and the algorithms implemented. In fact, we noticed that the standard classification algorithms are not fully suitable for the fraud detection problem (as the cost of every individual false negative can be different from the others), and we looked for alternative methods, especially the meta-heuristics. Among them the newly introduced migrating birds optimization algorithm (MBO) turned out to be superior and was implemented. In addition, during the study a cost sensitive decision tree algorithm was developed and introduced to the literature.