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.
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Journal of Business and Economics Research, 2010, 8 (7), pp.75-83. 〈http://www.cluteinstitute.com/ojs/index.php/JBER/article/view/744/729〉
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Dominique Geyer. Detecting fraud in financial data sets. Journal of Business and Economics Research, 2010, 8 (7), pp.75-83. 〈http://www.cluteinstitute.com/ojs/index.php/JBER/article/view/744/729〉. 〈hal-00796943〉

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