Fraud detection using predictive modeling

Data processing: financial – business practice – management – or co – Automated electrical financial or business practice or...

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G06F15700

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active

058192263

ABSTRACT:
An automated system and method detects fraudulent transactions using a predictive model such as a neural network to evaluate individual customer accounts and identify potentially fraudulent transactions based on learned relationships among known variables. The system may also output reason codes indicating relative contributions of various variables to a particular result. The system periodically monitors its performance and redevelops the model when performance drops below a predetermined level.

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Gullo, Karen, "Neural Nets Versus Card Fraud Chase's Software Learns to Detect Potential Crime" Feb. 2, 1990 American Banker Magazine .
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Rumelhart, K.E., et al., "Learning Representations by Back-Propagating Errors" Nature v. 323, pp. 533-536 (1986).
Hecht-Nielsen, R., "Theory of the Backpropagation Neural Network", Neural Networks for Perception pp. 65-93 (1992).
Weigend, A.S., et al., "Generalization by Weight-Elimination with Application to Forecasting", Advances in Neural Information Processing Systems 3 pp. 875-882.

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