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Using Benford'S Law To The Detection Of Misrepresentation Of Financial Statements Data

Author

Listed:
  • Radoslav Tusan

    (Technical University of Košice Faculty of Economics)

Abstract

Benford's Law is in certain situations, an important instrument to detect deliberate misrepresentation in the financial statements. Benford's Law is empirically derived and verified rule that the numerical data beginning with the digit by any of the groups 1, 2, ...9 appear in the files of large size with a certain probability. The likelihood of occurrence of numerical data in large data files according to the first numbers varies considerably. Numbers beginning with a digit 1 occur with a probability of 30.1%, numbers beginning with a digit 9 appear in this set with a probability of 4.58%. These values can be incorporated into the control procedures for assessing the quality of the reference data set. Various foreign authors have pointed out the possibility of using Benford's Law in examining the quality of primary data in the field of accounting and reporting. The authors investigated the differences between the empirical and theoretical frequency of occurrence of each number beginning with individual digits in financial reporting. Benford's analysis according them is more reliable when applied to the entire set of data. The intention of the article is to point out the possible misrepresentation in the financial statements of the registered entity whose shares are traded on the domestic stock exchange. One of the reasons for the detection of misrepresentation is that investors trust the financial statements of these entities. The research question was whether Benford's Law reveals the possible manipulation of financial statements data. The source data were financial statements of the entity for three years: balance sheet, income statement and cash flow statement. The number of each leading digit was counted and the actual frequency of leading digits to the expected distribution according to Benford's Law was compared. Potential manipulation was calculated by means of Kolmogorov-Smirnov statistics. Results of the analysis are mainly addressed to users of information of financial statements and confirmed the importance of Benford's Law in this meaning.

Suggested Citation

  • Radoslav Tusan, 2016. "Using Benford'S Law To The Detection Of Misrepresentation Of Financial Statements Data," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 737-745, July.
    • Handle: RePEc:ora:journl:v:1:y:2016:i:1:p:737-745
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    File URL: http://anale.steconomiceuoradea.ro/volume/2016/n1/66.pdf
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    References listed on IDEAS

    as
    1. Tam Cho, Wendy K. & Gaines, Brian J., 2007. "Breaking the (Benford) Law: Statistical Fraud Detection in Campaign Finance," The American Statistician, American Statistical Association, vol. 61, pages 218-223, August.
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    More about this item

    Keywords

    Benfords Law; reporting; financial statements;
    All these keywords.

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting

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