Detecting fraud in financial data sets

Dominique Geyer ()
Additional contact information
Dominique Geyer: Audencia Recherche - Audencia Business School

Post-Print from HAL

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.

Keywords: Income statement manipulation; Cheating behaviour and Benford's law; Accounting fraud; Internal auditing (search for similar items in EconPapers)
Date: 2010
Note: View the original document on HAL open archive server: https://audencia.hal.science/hal-00796943
References: View references in EconPapers View complete reference list from CitEc
Citations:

Published in Journal of Business and Economics Research, 2010, 8 (7), pp.75-83

Downloads: (external link)
https://audencia.hal.science/hal-00796943/document (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-00796943

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().