Ensemble Learning in Credit Card Fraud Detection Using Boosting Methods

Abstract

With the continuous prosperity of the financial market, credit card volume has always been booming these years. The fraud businesses are also raising rapidly. Under this circumstance, fraud detection has become a more and more valuable problem. But the proportion of the fraud is absolutely much lower than the genius transaction, so the imbalance dataset makes this problem much more challenging. In this paper we mainly tell how to cope with the credit card fraud detection problem by using boosting methods and also gave a contribution of the brief comparison between these boosting methods.