Neural data mining for credit card fraud detection
Rüdiger W. Brause, T. Langsdorf, Martin F. Hepp · 2003
The prevention of credit card fraud is an important application for prediction techniques. One major obstacle for using neural network training techniques is the high necessary diagnostic quality: since only one financial transaction in a thousand is invalid no prediction success less than 99.9% is acceptable. Because of these credit card transaction requirements, completely new concepts had to be developed and tested on real credit card data. This paper shows how advanced data mining techniques and a neural network algorithm can be combined successfully to obtain a high fraud coverage combined with a low false alarm rate.