INTRODUCTION
Unlawful or unfair gain by deliberate deception is termed in law, as fraud. Fraud is both a civil wrong (i.e., a fraud victim is eligible for monetary compensation and/may sue the perpetrator to avoid the fraud) and a criminal wrong (i.e., the fraud perpetrator can be prosecuted and subsequently imprisoned by governmental authorities). Fraud may have various purposes such as monetary gain or other benefits, like obtaining a driver’s license by way of false statements. [1]
Fraud has a common occurrence in the buying or selling of property, including real estate, Personal Property, and intangible property, such as stocks, bonds, and copyrights. Fraud is criminalized by State and Federal Statutes, but not all cases rise to the level
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Four journal databases, including IEEE Transactions, Science Direct, SPRINGER and J-Gate, were searched for against the keywords “fraud”, “fraud detection” and “data mining” to yield appropriate results. The “fraud” and “fraud detection” descriptors cover all the various categories of fraud including (but not limited to) insurance fraud, telecommunications fraud, bank fraud, and credit card fraud. The absence of specific keywords such as “credit card fraud”, “insurance fraud”, etc. allowed the data set to remain unbiased towards any particular category. This search yielded approximately 800 articles, which were further analysed by the authors to ensure that only the most relevant articles, i.e. articles researching applications of data mining to fraud detection, were chosen. Other criteria applied during selection included year of publishing, as only articles during the years 2008-2015 were chosen, and availability. Unpublished working papers, textbook extracts and conference papers were excluded as their full texts are not currently available. In the end only full text, published articles were chosen for the study.
In final research analysis (detailed explanation in Section_) certain papers were analysed and their research was summarized in order to aid further research. The framework for classification of research papers is depicted in fig.