Using Statistical Methods to Screen for Earnings Manipulation and Corporate Fraud

Jesper Sørensen ()

Chapter Chapter 11 in Shorting Fraud, 2025, pp 111-124 from Springer

Abstract: Abstract This chapter explores statistical methods that may be used for screening for corporate fraud and earnings manipulation. It briefly discusses time series analysis, cross-sectional analysis and TSCS analysis for corporate fraud detection. Then the chapter details practical models like the Beneish M-Score, Montier C-score, Sloan Accruals Ratio, etc., explaining their calculations and interpretations. It also introduces Benford’s Law, a principle used to detect anomalies in financial data, and the AB-Score and ABF-Score, which build upon Benford’s Law and the Dechow F-Score. Finally, the chapter touches briefly on other statistical tools like the Z-Score, Chi-square test, Runs test, and multivariate analysis as building blocks for corporate fraud detection.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-81834-9_11

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DOI: 10.1007/978-3-031-81834-9_11

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