Credit card fraud detection by adaptive neural data mining

  • 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.

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Author:Rüdiger W. BrauseGND, Timm Sebastian Langsdorf, Hans-Michael Hepp
Parent Title (German):Universität Frankfurt am Main. Fachbereich Informatik: Interner Bericht ; 99,7
Series (Serial Number):Interner Bericht / Fachbereich Informatik, Johann Wolfgang Goethe-Universität Frankfurt a.M. (99,7)
Document Type:Report
Year of Completion:1999
Year of first Publication:1999
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2009/07/14
Institutes:Informatik und Mathematik / Informatik
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):License LogoDeutsches Urheberrecht