Open Access
August 2002 Statistical Fraud Detection: A Review
Richard J. Bolton, David J. Hand
Statist. Sci. 17(3): 235-255 (August 2002). DOI: 10.1214/ss/1042727940


Fraud is increasing dramatically with the expansion of modern technology and the global superhighways of communication, resulting in the loss of billions of dollars worldwide each year. Although prevention technologies are the best way to reduce fraud, fraudsters are adaptive and, given time, will usually find ways to circumvent such measures. Methodologies for the detection of fraud are essential if we are to catch fraudsters once fraud prevention has failed. Statistics and machine learning provide effective technologies for fraud detection and have been applied successfully to detect activities such as money laundering, e-commerce credit card fraud, telecommunications fraud and computer intrusion, to name but a few. We describe the tools available for statistical fraud detection and the areas in which fraud detection technologies are most used.


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Richard J. Bolton. David J. Hand. "Statistical Fraud Detection: A Review." Statist. Sci. 17 (3) 235 - 255, August 2002.


Published: August 2002
First available in Project Euclid: 16 January 2003

zbMATH: 1013.62115
MathSciNet: MR1963313
Digital Object Identifier: 10.1214/ss/1042727940

Keywords: computer intrusion , credit cards , e-commerce , Fraud detection , fraud prevention , machine learning , money laundering , statistics , telecommunications

Rights: Copyright © 2002 Institute of Mathematical Statistics

Vol.17 • No. 3 • August 2002
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