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Fuzzy Ranking of Financial Statements for Fraud Detection

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3 Author(s)
Wei Chai ; Gen. Electr. Global Res., Niskayuna ; B. K. Hoogs ; B. T. Verschueren

Automatic detection of anomalies in financial statements can decrease the risk of exposure to fraudulent corporate behavior. This paper proposes a method to convert fraud classification rules learned from a genetic algorithm to a fuzzy score representing the degree to which a company's financial statements match those rules. Applying the method to financial data in real time can lead to the early detection of potentially fraudulent corporate behavior.

Published in:

2006 IEEE International Conference on Fuzzy Systems

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