Benford's Law and Fraud Detection. Facts and Legends
AbstractIs Benford's law a good instrument to detect fraud in reports of statistical and scientific data? For a valid test the probability of "false positives" and "false negatives" has to be low. However, it is very doubtful whether the Benford distribution is an appropriate tool to discriminate between manipulated and non-manipulated estimates. Further research should focus more on the validity of the test and test results should be interpreted more carefully.
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Bibliographic InfoPaper provided by ETH Zurich, Chair of Sociology in its series ETH Zurich Sociology Working Papers with number 8.
Length: 8 pages
Date of creation: 06 Feb 2010
Date of revision:
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Benford's law; fraud detection; false positive; false negative; regression coefficients;
Other versions of this item:
- Andreas Diekmann & Ben Jann, 2010. "Benford's Law and Fraud Detection: Facts and Legends," German Economic Review, Verein für Socialpolitik, vol. 11, pages 397-401, 08.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-02-27 (All new papers)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Andreas Diekmann, 2007.
"Not the First Digit! Using Benford's Law to Detect Fraudulent Scientif ic Data,"
Journal of Applied Statistics,
Taylor & Francis Journals, vol. 34(3), pages 321-329.
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- Susumu Shikano & Verena Mack, 2011. "When Does the Second-Digit Benford’s Law-Test Signal an Election Fraud? Facts or Misleading Test Results," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 231(5-6), pages 719-732, November.
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