Beneish M-Score Reliability as a Tool For Detecting Financial Statements Fraud

Ria Septiani, Siti Musyarofah, Rita Yuliana

Abstract


The rise of fraud has made a reliable and precise fraud detection model based on financial reports critical to developing. This study uses discriminant analysis to test the Beneish M-Score's ability in detecting fraud in the presentation of financial statements with a sample of 114 financial statements of banking companies for 2016-2018. The study results using the discriminant analysis method found that the beneish m-score was able to detect fraud by 89.5%. Meanwhile, the Beneish DSRI, GMI, AQI, DPI, and TATA ratios prove significant in grouping companies into manipulators and non-manipulators. This research concludes that the Beneish M-Score model is accurate in detecting fraud in its financial statements. The Beneish M-Score ratios contributing to grouping financial reports into the companies' manipulator and non-manipulator companies are DSRI, GMI, AQI, DPI, and TATA. DSRI is the most dominant ratio in grouping these companies.

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References


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