Association rules applied to credit card fraud detection

Authors:
D. Sánchez;M. A. Vila;L. Cerda;J. M. Serrano
Affiliations:
Department of Computer Science, A.I., University of Granada, E.T.S.I. Informática y Telecomunicación, C/Periodista Daniel Saucedo Aranda s/n, 18071 Granada, Spain;Department of Computer Science, A.I., University of Granada, E.T.S.I. Informática y Telecomunicación, C/Periodista Daniel Saucedo Aranda s/n, 18071 Granada, Spain;Department of Computer Science, A.I., University of Granada, E.T.S.I. Informática y Telecomunicación, C/Periodista Daniel Saucedo Aranda s/n, 18071 Granada, Spain;Department of Informatics, University of Jaen, Spain
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

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Abstract

Association rules are considered to be the best studied models for data mining. In this article, we propose their use in order to extract knowledge so that normal behavior patterns may be obtained in unlawful transactions from transactional credit card databases in order to detect and prevent fraud. The proposed methodology has been applied on data about credit card fraud in some of the most important retail companies in Chile.