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Winter, C, Schneider, M and Yannikos, Y (2011)

Detecting Fraud Using Modified Benford Analysis

Advances in Digital Forensics VII, 7th IFIP WG 11.9 International Conference on Digital Forensics, Orlando, FL, USA, January 31 February 2, 2011, Revised Selected Papers. Gilbert Peterson and Sujeet Shenoi (Editors). IFIP Advances in Information and Co.

ISSN/ISBN: 1868-4238 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.


Bibtex:
@inproceedings{, author = {Winter, Christian AND Schneider, Markus AND Yannikos, York}, title = {Detecting Fraud Using Modified {Benford} Analysis}, booktitle = {Advances in Digital Forensics VII}, booksubtitle = {7th IFIP WG 11.9 International Conference on Digital Forensics, Orlando, FL, USA, January 31 -- February 2, 2011, Revised Selected Papers}, editor = {Peterson, Gilbert L. AND Shenoi, Sujeet}, publisher = {Springer}, series = {IFIP Advances in Information and Communication Technology}, seriesshort = {IFIP AICT}, volume = {361}, pages = {129--141}, month = {oct}, year = {2011}, }


Reference Type: Conference Paper

Subject Area(s): Accounting, Statistics