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Neural data mining for credit card fraud detection
Abstract
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.
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Citations
Cited by
Chandola, V., Banerjee, A., & Kumar, V. (2009) · ACM Computing Surveys · doi:10.1145/1541880.1541882 · Cited by 11,687
Statistical Fraud Detection: A Review
Bolton, R. J., & Hand, D. J. (2002) · Statistical Science · doi:10.1214/ss/1042727940 · Cited by 1,450
Data mining for credit card fraud: a comparative study
Bhattacharyya, S., Jha, S., Tharakunnel, K., & Westland, J. C. (2011) · Decision Support Systems · doi:10.1016/j.dss.2010.08.008 · Cited by 1,108
Fraud detection system: A survey
Abdallah, A., Maarof, M. A., & Zainal, A. (2016) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2016.04.007 · Cited by 708
Feature engineering strategies for credit card fraud detection
Correa Bahnsen, A., Aouada, D., Stojanovic, A., & Ottersten, B. (2016) · Expert Systems with Applications · doi:10.1016/j.eswa.2015.12.030 · Cited by 451
Metadata
- Authors
- Brause, R., Langsdorf, T., & Hepp, M.
- Venue
- Proceedings 11th International Conference on Tools with Artificial Intelligence
- Publisher
- IEEE Comput. Soc
- Published
- 2003-01-20
- Pages
- 103-106
- OpenAlex
- W2105809068
- Cited by
- 361
- References
- 0
- FWCI
- 4.91
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Brause, R., Langsdorf, T., & Hepp, M. (2003). Neural data mining for credit card fraud detection. Proceedings 11th International Conference on Tools with Artificial Intelligence. https://doi.org/10.1109/tai.1999.809773
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