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Detecting fraud in financial data sets

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  • Dominique Geyer

    (Audencia Recherche - Audencia Business School)

Abstract

An important neef of corporations for internal audits is the ability to detect fraudulently reported financial data. Benford's Law is a probability distribution which is useful to analyse patterns of digits in numbers sets. A history of the origins of Benford's Law is given and the types of data sets expected to follow Benford's Law is discussed. This paper examines how BA students falsify financial numbers. The paper shows that they fail to imitate Benford's law and that there are cheating behaviour patterns coherent with previous empirical studies.

Suggested Citation

  • Dominique Geyer, 2010. "Detecting fraud in financial data sets," Post-Print hal-00796943, HAL.
    • Handle: RePEc:hal:journl:hal-00796943
    Note: View the original document on HAL open archive server: https://audencia.hal.science/hal-00796943
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    References listed on IDEAS

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    1. Dollar, David & Fisman, Raymond & Gatti, Roberta, 2001. "Are women really the "fairer" sex? Corruption and women in government," Journal of Economic Behavior & Organization, Elsevier, vol. 46(4), pages 423-429, December.
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