Data Mining and Economic Crime Risk Management

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Author(s): Mieke Jans (Hasselt University, Belgium), Nadine Lybaert (Hasselt University, Belgium)and Koen Vanhoof (Hasselt University, Belgium)
Copyright: 2011
Pages: 23
Source title: Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection
Source Author(s)/Editor(s): Ali Serhan Koyuncugil (Capital Markets Board of Turkey, Turkey, and Baskent University, Turkey)and Nermin Ozgulbas (Baskent University, Turkey)
DOI: 10.4018/978-1-61692-865-0.ch011

Keywords: Information Science Reference / Information Security & Privacy / IT Security and Ethics / Security & Forensics

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Abstract

Economic crime is a billion dollar business and is substantially present in our current society. Both researchers and practitioners have gone into this problem by looking for ways of fraud mitigation. Data mining is often called in this context. In this chapter, the application of data mining in the field of economic crime, or corporate fraud, is discussed. The classification external versus internal fraud is explained and the major types of fraud within these classifications will be given. Aside from explaining these classifications, some numbers and statistics are provided. After this thorough introduction into fraud, an academic literature review concerning data mining in combination with fraud is given, along with the current solutions for corporate fraud in business practice. At the end, a current state of data mining applications within the field of economic crime, both in the academic world and in business practice, is given.

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