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Geyer, D (2010)

Detecting fraud in financial data sets

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

ISSN/ISBN: Not available at this time. DOI: Not available at this time.



Abstract: An important need of corporations for internal audits is the ability to detect fraudulently reported financial data. Benfordís Law is a numerical phenomenon in which sets of data that are counting or measuring some event follow a certain distribution. A history of the origins of Benfordís Law is given and the types of data sets expected to follow Benfordís Law is discussed. This paper examines how a sample of students falsify financial numbers. The paper shows that they fail to imitate Benfordís law and that there are cheating behaviour patterns coherent with previous empirical studies.


Bibtex:
@article {, AUTHOR = {Dominique Geyer}, TITLE = {Detecting fraud in financial data sets}, JOURNAL = {Journal of Business and Economics Research}, YEAR = {2010}, VOLUME = {8}, NUMBER = {7}, PAGES = {75--83}, DOI = {}, URL = {https://pdfs.semanticscholar.org/a205/bc874d0fb282af2b1b2a43bf956ceed713d4.pdf}, }


Reference Type: Journal Article

Subject Area(s): Economics