Detecting Fraud Using Modified Benford Analysis - Advances in Digital Forensics VII
Conference Papers Year : 2011

Detecting Fraud Using Modified Benford Analysis

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.
Fichier principal
Vignette du fichier
978-3-642-24212-0_10_Chapter.pdf (352.34 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-01569557 , version 1 (27-07-2017)

Licence

Identifiers

Cite

Christian Winter, Markus Schneider, York Yannikos. Detecting Fraud Using Modified Benford Analysis. 7th Digital Forensics (DF), Jan 2011, Orlando, FL, United States. pp.129-141, ⟨10.1007/978-3-642-24212-0_10⟩. ⟨hal-01569557⟩
72 View
471 Download

Altmetric

Share

More