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Application of Beneish M-Score Models and Data Mining to Detect Financial Fraud

154 citations0/0 files storedProcedia - Social and Behavioral Sciences

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Auditing, Earnings Management, Governance Corporate Governance and Financial Management Benford’s Law and Fraud Detection

Abstract

This study aims to analyze the ability of m-score Beneish in detecting financial fraud. This research data refer to companies that commit fraud according to the fraud Database of Sanctions of Issuer Cases Public Companies that was released by the Financial Services Authority in the period of 2001-2014. The results showed that overall Beneish m-score model was capable to detect financial fraud. Gross margin index, depreciation index, index of sales and general administrative burden and total accruals were all significant in detecting financial fraud. Sales index, asset quality index, and leverage index was statistically not significant in detecting financial fraud.

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References

1997An Empirical Analysis of the Relation between the Board of Director Composition and Financial Statement Fraud 1999The Detection of Earnings Manipulation 2002Detecting false financial statements using published data: some evidence from Greece 2011Using Financial Statement Data To Identify Factors Associated With Fraudulent Financial Reporting 2004Can financial ratios detect fraudulent financial reporting?

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2019Manajemen Laba: Ukuran Perusahaan, Kepemilikan Manajerial dan Kompensasi Bonus 2020The Influence of Corporate Governance on the Mitigation of Fraudulent Financial Reporting 2020Using the Beneish M-score model: Evidence from non-financial companies listed on the Warsaw Stock Exchange 2021Corporate governance and fraudulent financial reporting 2021Scoring the financial distress and the financial statement fraud of Garuda Indonesia with «DDCC» as the financial solutions 2023Impact of earnings management on working capital management efficiency 2019EFEKTIVITAS MODEL BENEISH M-SCORE DAN MODEL F-SCORE DALAM MENDETEKSI KECURANGAN LAPORAN KEUANGAN

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