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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/10227

Title: Internal fraud risk reduction by data mining and process mining: framework and case study
Authors: Jans, Mieke
Advisors: Lybaert, Nadine
Vanhoof, Koen
Issue Date: 2009
Publisher: UHasselt Diepenbeek
Abstract: The lack of data analysis research on internal fraud in the academic field, is an opportunity to devote attention to. We decide to focus our research objective on internal fraud, with transaction fraud (not investigated at all) being a part of this. That internal fraud is worth investigating, is already touched upon in section 1.1.5. The average financial damage to companies subjected to the PwC survey, was US$ 2.42 million per company and participants of the ACFE study estimated a loss of 7% of a company's annual revenues to fraud. Also Lynch and Gomaa (2003) draw attention to the susceptibility of organizations to fraudulent employee behavior. The authors state that with the integration of advanced information technology (IT) into business organizations, unintended risks and consequences can be introduced into the business environment. Internal fraud has received a great deal of attention from interested parties like governments or non-profit institutions. The emergence of fraud into our economic world didn't go unnoticed. A US fraud standard (SAS 99) and an international counterpart (ISA 240) were created. Section 404 of the Sarbanes-Oxley act of 2002 also addresses this issue. Meanwhile, the CEO's of the International Audit Networks released a special report in November 2006. This report, issued by the six largest global audit networks, is released in the wake of corporate scandals. The authors of this report express their believe in fighting fraud, as they name it "one of the six vital elements, necessary for capital market stability, efficiency and growth". Unlike most fraud literature in academic fields, this report addresses internal fraud. Another aspect a decision is made about, is the exact delineation of fraud research in this dissertation. One can focus on the factors that influence fraud, determinants that can be used to investigate fraud, fraud detection techniques, or fraud prevention mechanisms. This dissertation will aim at the combination of fraud detection and prevention, which will be referred to as 'fraud risk reduction'. This decision is corresponding with the ideas of Davia et al. (2000) and Bologna and Lindquist (1995), that fraud prevention and fraud detection should complement each other. Based on the absence of a methodological framework to mitigate internal fraud in the academic literature, the cost internal fraud nevertheless presents, and the clear interest the business environment shows, the research objective is to present and to apply a framework for internal fraud risk reduction. For this purpose, two courses are followed. We first have a look at what already exists in the business environment to prevent and detect internal fraud. Next, we turn to the methodology followed in the academic field with respect to external fraud. Particularly the use of data mining techniques are considered as a valuable contribution, since it has proven its value in mitigating external fraud. In the following chapter these two courses are explored, followed by the resulting framework for internal fraud risk reduction, the core of this dissertation.
Notes: doctoraat toegepaste economische wetenschappen
URI: http://hdl.handle.net/1942/10227
Category: T1
Type: Theses and Dissertations
Appears in Collections: PhD theses
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