Data Mining and Economic Crime Risk Management

Data Mining and Economic Crime Risk Management

Mieke Jans (Hasselt University, Belgium), Nadine Lybaert (Hasselt University, Belgium) and Koen Vanhoof (Hasselt University, Belgium)
DOI: 10.4018/978-1-61692-865-0.ch011
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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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What is Economic Crime?

There are many definitions of fraud, depending on the point of view considering. According to The American Heritage Dictionary, (Third Edition), fraud is defined as “a deception deliberately practiced in order to secure unfair or unlawful gain” (p.722). We can conclude that fraud is deception. Whatever industry the fraud is situated in or whatever kind of fraud you visualize, deception is always the core of fraud.

In a nutshell, Davia, et al. (2000) summarize: “Fraud always involves one or more persons who, with intent, act secretly to deprive another of something of value, for their own enrichment”. Also Wells (2005) stresses deception as the linchpin to fraud.

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Table of Contents
David J. Hand
Ali Serhan Koyuncugil, Nermin Ozgulbas
Ali Serhan Koyuncugil, Nermin Ozgulbas
Chapter 1
Inci Batmaz, Güser Köksal
Development of more effective early warning systems (EWSs) for various applications have been possible during the past decade due to advancements in... Sample PDF
Overview of Knowledge Discovery in Databases Process and Data Mining for Surveillance Technologies and EWS
Chapter 2
Armand Faganel, Danijel Bratina
Modern data mining tools search databases for hidden patterns, finding predictive information that is otherwise not evident. There exist four models... Sample PDF
Data Mining and Privacy Protection
Chapter 3
Vassiliy Simchera, Ali Serhan Koyuncugil
Besides the well-known commonplace, and sometimes also simply fantastic reasons for the existing breaks in the estimations of one and the same... Sample PDF
On the Nature and Scales of Statistical Estimations Divergence and its Linkage with Statistical Learning
Chapter 4
Tze Leung Lai, Bo Shen
This chapter gives a review of recent developments in sequential surveillance and modeling of default probabilities of corporate and retail loans... Sample PDF
Black-Necked Swans and Active Risk Management
Chapter 5
Nermin Ozgulbas, Ali Serhan Koyuncugil
Risk management has become a vital topic for all enterprises especially in financial crisis periods. All enterprises need systems to warn against... Sample PDF
Financial Early Warning System for Risk Detection and Prevention from Financial Crisis
Chapter 6
Murat Acar, Dilek Karahoca, Adem Karahoca
This chapter focuses on building a financial early warning system (EWS) to predict stock market crashes by using stock market volatility and rising... Sample PDF
Designing an Early Warning System for Stock Market Crashes by Using ANFIS
Chapter 7
Chih-Fong Tsai, Yu-Hsin Lu, Yu-Feng Hsu
It is very important for financial institutions which are capable of accurately predicting business failure. In literature, numbers of bankruptcy... Sample PDF
Bankruptcy Prediction by Supervised Machine Learning Techniques: A Comparative Study
Chapter 8
Laura Giurca Vasilescu, Marian Siminica, Cerasela Pirvu, Costel Ionascu, Anca Mehedintu
The small and medium enterprises (SMEs) represent the backbone of the economy, playing a major economic and social role in the process of developing... Sample PDF
Data Mining Used for Analyzing the Bankruptcy Risk of the Romanian SMEs
Chapter 9
Ali Serhan Koyuncugil, Nermin Ozgulbas
After last global financial crisis, one of the most important concerns of the governments became unemployment. Higher unemployment rates haves been... Sample PDF
Social Aid Fraud Detection System and Poverty Map Model Suggestion Based on Data Mining for Social Risk Mitigation
Chapter 10
Chia-Hui Wang, Ray-I Chang, Jan-Ming Ho
Thanks to fast technology advancement of micro-electronics, wired/wireless networks and computer computations in past few years, the development of... Sample PDF
Collaborative Video Surveillance for Distributed Visual Data Mining of Potential Risk and Crime Detection
Chapter 11
Mieke Jans, Nadine Lybaert, Koen Vanhoof
Economic crime is a billion dollar business and is substantially present in our current society. Both researchers and practitioners have gone into... Sample PDF
Data Mining and Economic Crime Risk Management
Chapter 12
Ibrahim George, Manolya Kavakli
In this chapter, the authors explore the operational data related to transactions in a financial organisation to find out the suitable techniques to... Sample PDF
Data Mining in the Investigation of Money Laundering and Terrorist Financing
Chapter 13
Rosaria Lombardo
By the early 1990s, the term “data mining” had come to mean the process of finding information in large data sets. In the framework of the Total... Sample PDF
Data Mining and Explorative Multivariate Data Analysis for Customer Satisfaction Study
Chapter 14
Danijel Bratina, Armand Faganel
Price promotions have been largely dealt with in the literature. Yet there are just a few generalizations made so far about this powerful marketing... Sample PDF
Using POS Data for Price Promotions Evaluation: An Empirical Example from a Slovenian Grocery Chain
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