Procedia - Social and Behavioral Sciences · 2015 · 149 citations · 11 references
BusinessAccountancyFinanceData MiningFinancial AccountingFinancial AnalyticsFinancial Statement FraudFraud DetectionFraud ExaminationFraud InvestigationFraud PreventionFraud Risk AnalyticsData Mining In AuditingFinancial Fraud InvestigationFinancial Statement Fraud DetectionFraud Detection MetricsFraud Pattern MiningFraud Risk ModelingFraud Scoring ModelsTotal Accruals
The study evaluates the effectiveness of the Beneish M‑Score in detecting financial fraud. The analysis uses fraud‑flagged companies from the Financial Services Authority’s 2001‑2014 Sanctions Database. The Beneish M‑Score successfully identified fraud, with gross margin, depreciation, sales, G&A burden, and total accrual indices significant, while sales, asset quality, and leverage indices were not.
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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The Detection of Earnings Manipulation
Messod D. Beneish · Financial Analysts Journal · 1999 · 1.3K citations
Business, Accountancy, Accounting +12