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Credit card fraud detection with a neural-network

Ghosh, Reilly·1994·Proceedings of the Twenty-Seventh Hawaii International Conference on System Sciences HICSS-94

Abstract

Using data from a credit card issuer, a neural network based fraud detection system was trained on a large sample of labelled credit card account transactions and tested on a holdout data set that consisted of all account activity over a subsequent two-month period of time. The neural network was trained on examples of fraud due to lost cards, stolen cards, application fraud, counterfeit fraud, mail-order fraud and NRI (non-received issue) fraud. The network detected significantly more fraud accounts (an order of magnitude more) with significantly fewer false positives (reduced by a factor of 20) over rule-based fraud detection procedures. We discuss the performance of the network on this data set in terms of detection accuracy and earliness of fraud detection. The system has been installed on an IBM 3090 at Mellon Bank and is currently in use for fraud detection on that bank's credit card portfolio.>

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Metadata

Authors
Ghosh, & Reilly
Venue
Proceedings of the Twenty-Seventh Hawaii International Conference on System Sciences HICSS-94
Published
1994
Pages
621-630
OpenAlex
W2074346829
Cited by
433
References
0
FWCI
1.25
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Credit card fraud detection with a neural-network. https://app.cochat.ai/papers/10.1109/hicss.1994.323314
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Ghosh, & Reilly. (1994). Credit card fraud detection with a neural-network. Proceedings of the Twenty-Seventh Hawaii International Conference on System Sciences HICSS-94. https://doi.org/10.1109/hicss.1994.323314

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