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|Title: ||Data Mining and Economic Crime Risk Management|
|Authors: ||JANS, Mieke|
|Issue Date: ||2011|
|Publisher: ||Information Science Reference|
|Citation: ||Koyuncugil, Ali Serhan & Ozgulbas, Nermin (Ed.) Surveillance technologies and early warning systems: Data mining applications for risk detection, p. 205-227.|
|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.|
|Type: ||Book Section|
|Validation: ||vabb, 2017|
|Appears in Collections: ||Research publications|
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