Overcoming selectivity bias in evaluating new fraud detection systems for revolving credit operations

David J. Hand and Martin J. Crowder

International Journal of Forecasting, 2012, vol. 28, issue 1, 216-223

Abstract: When proposed new fraud detection systems are tested in revolving credit operations, a straightforward comparison of the observed fraud detection rates is subject to a selectivity bias that tends to favour the existing system. This bias arises from the fact that accounts are terminated when the existing system, but not the proposed new system, detects a fraudulent transaction. This therefore flatters the estimated detection rate of the existing system. We develop more formal estimators that can be used to compare the existing and proposed new systems without risking this effect. We also assess the magnitude of the bias.

Keywords: Financial fraud; Fraud detection; Fraud estimation (search for similar items in EconPapers)
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:28:y:2012:i:1:p:216-223

DOI: 10.1016/j.ijforecast.2010.10.005

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