Triage in forensic accounting using Zipf's law

Adeola Odueke, George Weir

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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n forensic accounting, use of Benford's law has long been acknowledged as a technique for identifying anomalous numerical data. Zipf's law has received considerably less attention in this domain despite the fact that it is not limited to analysis of numerical datasets. The present paper outlines the context of fraud detection and then describes an experiment that contrasted Benford's law and Zipf's law as highlighters for data anomaly, with a view to enhancing current techniques in fraud detection. Results from tests on two datasets using each technique showed similarities in the samples characterized as 'fraudulent' from which we propose that, when combined with its extended realm of data applicability, Zipf's law has significant potential as an aid to fraud detection as a supplement to other analysis techniques. In particular, this approach could be employed as a component in forensic accounting triage in order to enhance the detection rate of fraud and assist in fraud prevention.
Original languageEnglish
Title of host publicationIssues in Cybercrime, Security and Digital Forensics
EditorsGeorge Weir, Ameer Al-Nemrat
Place of PublicationGlasgow
Number of pages11
Publication statusPublished - 2012


  • forensic accounting
  • Benfor's law
  • Zipf's law
  • triage


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