An Analysis of Data Mining Applications for Fraud Detection in Securities Market

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Provided by: IIR Publications
Topic: Security
Format: PDF
In recent securities fraud broadly refers to deceptive practices in connection with the offering for sale of securities. There are many challenges involved in developing data mining applications for fraud detection in securities market, including: massive datasets, accuracy, privacy, performance measures and complexity. The impacts on the market and the training of regulators are other issues that need to be addressed. In this paper, the authors present the results of a comprehensive systematic literature review on data mining techniques for detecting fraudulent activities and market manipulation in securities market.
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