Skip to Main content Skip to Navigation
New interface
Journal articles

Detecting fraud in financial data sets

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.
Document type :
Journal articles
Complete list of metadata

Cited literature [16 references]  Display  Hide  Download
Contributor : Sylvia Cheminel Connect in order to contact the contributor
Submitted on : Friday, February 21, 2014 - 4:21:02 PM
Last modification on : Saturday, November 19, 2016 - 1:11:21 AM
Long-term archiving on: : Wednesday, May 21, 2014 - 10:36:38 AM


Files produced by the author(s)


  • HAL Id : hal-00796943, version 1



Dominique Geyer. Detecting fraud in financial data sets. Journal of Business and Economics Research, 2010, 8 (7), pp.75-83. ⟨hal-00796943⟩



Record views


Files downloads