Accuracy evaluation of a credit card fraud detection system on Hadoop MapReduce

In digitalization era, credit card fraud detection is of high significance to financial organizations. This paper discussed about credit card fraud detection by parallelizing of Negative Selection Algorithm on the Cloud computing platform. We present performance evaluation of running the algorithm on the cloud by MapReduce framework and show it´s dramatically results on real world financial data. We argue that, for the fraud detection rate, False Negative rate, fraud catching rate (True Positive rate) and false alarm rate (False Positive rate), Cost and Hit rate that are the best metrics for a desirable credit card fraud detection system.