Document Server@UHasselt >
Research >
Research publications >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/11479

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.
URI: http://hdl.handle.net/1942/11479
ISBN: 978-1-61692-865-0
Category: B2
Type: Book Section
Validation: vabb, 2017
Appears in Collections: Research publications

Files in This Item:

There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.