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Entropic Analysis in Financial Forensics

Author

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  • Y V Reddy
  • A Sebastin

Abstract

Digital analysis has become an accepted tool for computer forensic examination of suspicious financial transactions. A major component of digital analysis is Benford’s Law which postulates that in accounting data not subject to substantial error or fraud, significant digits are not uniformly distributed and that smaller digits occur more often than larger digits as significant digits. In this paper, entropy-based mutual information is proposed to decide whether a dataset conforms to Benford distribution or not. If the dataset is found to deviate from Benford distribution, further analysis may be made into the authenticity of data entries.

Suggested Citation

  • Y V Reddy & A Sebastin, 2012. "Entropic Analysis in Financial Forensics," The IUP Journal of Accounting Research and Audit Practices, IUP Publications, vol. 0(3), pages 42-57, July.
    • Handle: RePEc:icf:icfjar:v:11:y:2012:i:3:p:42-57
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    Cited by:

    1. Lin, Fengyi & Wu, Sheng-Fu, 2014. "Comparison of cosmetic earnings management for the developed markets and emerging markets: Some empirical evidence from the United States and Taiwan," Economic Modelling, Elsevier, vol. 36(C), pages 466-473.
    2. Edward J. Lusk & Michael Halperin, 2014. "Detecting Newcomb-Benford Digital Frequency Anomalies in the Audit Context: Suggested Chi2 Test Possibilities," Accounting and Finance Research, Sciedu Press, vol. 3(2), pages 191-191, May.

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