Winter, Christian ; Schneider, Markus ; Yannikos, York
Peterson, Gilbert ; Shenoi, Sujeet (eds.) (2011):
Detecting Fraud Using Modified Benford Analysis.
In: IFIP Advances in Information and Communication Technology, 361, In: Advances in Digital Forensics VII, Seventh IFIP WG 11.9 International Conference on Digital Forensics, Orlando, Florida, USA, January 30 – February 2, 2011, Revised Selected Papers, pp. 129–141,
Springer, USA, Florida, Orlando, National Center for Forensic Science, ISBN 978-3-642-24211-3,
DOI: 10.1007/978-3-642-24212-0_10,
[Conference or Workshop Item]

Abstract

Large enterprises frequently enforce accounting limits to reduce the impact of fraud. As a complement to accounting limits, auditors use Benford analysis to detect traces of undesirable or illegal activities in accounting data. Unfortunately, the two fraud fighting measures often do not work well together. Accounting limits may significantly disturb the digit distribution examined by Benford analysis, leading to high false alarm rates, additional investigations and, ultimately, higher costs. To better handle accounting limits, this paper describes a modified Benford analysis technique where a cut-off log-normal distribution derived from the accounting limits and other properties of the data replaces the distribution used in Benford analysis. Experiments with simulated and real-world data demonstrate that the modified Benford analysis technique significantly reduces false positive errors.

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