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Detecting Fraud Using Modified Benford Analysis

Winter, Christian ; Schneider, Markus ; Yannikos, York
eds.: Peterson, Gilbert ; Shenoi, Sujeet (2011)
Detecting Fraud Using Modified Benford Analysis.
USA, Florida, Orlando, National Center for Forensic Science
doi: 10.1007/978-3-642-24212-0_10
Conference or Workshop Item, Bibliographie

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.

Item Type: Conference or Workshop Item
Erschienen: 2011
Editors: Peterson, Gilbert ; Shenoi, Sujeet
Creators: Winter, Christian ; Schneider, Markus ; Yannikos, York
Type of entry: Bibliographie
Title: Detecting Fraud Using Modified Benford Analysis
Language: English
Date: October 2011
Publisher: Springer
Book Title: 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
Series: IFIP Advances in Information and Communication Technology
Series Volume: 361
Event Location: USA, Florida, Orlando, National Center for Forensic Science
DOI: 10.1007/978-3-642-24212-0_10
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.

Uncontrolled Keywords: Secure Data;Auditing, fraud detection, Benford analysis
Identification Number: TUD-CS-2011-0015
Divisions: LOEWE > LOEWE-Zentren > CASED – Center for Advanced Security Research Darmstadt
LOEWE > LOEWE-Zentren
LOEWE
Date Deposited: 30 Dec 2016 20:23
Last Modified: 17 May 2018 13:02
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