TY  - JOUR
A1  - Brause, Rüdiger W.
A1  - Langsdorf, Timm Sebastian
A1  - Hepp, Hans-Michael
T1  - Neural data mining for credit card fraud detection
N2  - 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 of a thousand is invalid no prediction success less than 99.9% is acceptable. Due to these credit card transaction proportions complete new concepts had to be developed and tested on real credit card data. This paper shows how advanced data mining techniques and neural network algorithm can be combined successfully to obtain a high fraud coverage combined with a low false alarm rate.
Y1  - 2010
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/7964
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30-79161
N1  - Postprint, zuerst in: IEEE Int. Conf. on Tools with Art. Intell. ICTAI-99, IEEE Press, 1999, S. 103-106
ER  -