Survey of Clustering based Financial Fraud Detection Research

Andrei Sorin Sabau ()

Informatica Economica, 2012, vol. 16, issue 1, 110-122

Abstract: Given the current global economic context, increasing efforts are being made to both prevent and detect fraud. This is a natural response to the ascendant trend in fraud activities recorded in the last couple of years, with a 13% increase only in 2011. Due to ever increasing volumes of data needed to be analyzed, data mining methods and techniques are being used more and more often. One domain data mining can excel at, suspicious transaction monitoring, has emerged for the first time as the most effective fraud detection method in 2011. Out of the available data mining techniques, clustering has proven itself a constant applied solution for detecting fraud. This paper surveys clustering techniques used in fraud detection over the last ten years, shortly reviewing each one.

Keywords: Fraud Detection; Data Mining; Clustering (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (2)

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