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I want to write my thesis about Fraud Detection in ERP Databases. I'm looking for a Industry Standard Processs such as CRISP-DM for Data Mining Projects, in order to justify my approach in solving the issue of finding outliers/anomalies in the data set. Is there any established Standard Process which would be more suitable for such an project?

Thanks.

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    $\begingroup$ what industry are you in? I imagine if standards exist, then they likely differ by subdomain, e.g., credit card fraud vs. insurance fraud $\endgroup$ – Brandon Loudermilk May 21 '16 at 14:21
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Here's a great book on Fraud Analytics. It's quite comprehensive and has a detailed list of original research references and other textbooks at the end of each chapter.

Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection Bart Baesens, Veronique Van Vlasselaer, Wouter Verbeke ISBN: 978-1-119-13312-4 Aug 2015

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You should refer this survey paper on Anomaly Detection (from University of Minnesota).

Please let me know if this helps you.

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  • $\begingroup$ The paper appears to be very encouraging. I'll get in touch later on as the paper is very comprehensive. $\endgroup$ – Nex May 23 '16 at 7:07

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