Sam Maes, Karl Tuyls, Bram Vanschoenwinkel, Bernard Manderick  Home/Search
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Abstract: This paper discusses automated credit card fraud detection by means of machine learning. In an era of digitalization, credit card fraud detection is of great importance to financial institutions. We apply two machine learning techniques suited for reasoning under uncertainty: artificial neural networks and Bayesian belief networks to the problem and show their significant results on real world financial data. Finally, future directions are indicated to improve both techniques and results. (Update)
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BibTeX entry: (Update)
@misc{ maes-credit,
author = "Sam Maes and Karl Tuyls and Bram Vanschoenwinkel and Bernard Manderick",
title = "Credit Card Fraud Detection Using Bayesian and Neural Networks",
url = "citeseer.ist.psu.edu/528278.html" }
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36 Toward scalable learning with non-uniform class and cost dis.. - Chan, Stolfo - 1998 DBLP
29 Credit card fraud detection using meta learning: Issues and .. - Chan, Stolfo et al. - 1997
21 Data Mining and Knowledge Discovery (context) - Fawcett, Provost - 1997 ACM
18 Learning Bayesian belief networks (context) - Lam, Bacchus
13 Neural Smithing: supervised learning in feed-forward (context) - Reed, Marks
4 Learning Bayesian networks from data: An ecient approach bas.. (context) - Cheng, Bell et al.
1 Machine Learning Techniques for Fraud Detection - Maes, Tuyls et al. - 2000
1 Kluwer Academic Publishers (context) - Fayyad, Mannila et al. - 1997
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