Evaluation of the Effectiveness of the Beneish M-Score Model as a Financial Statement Fraud Detection Tool
DOI:
https://doi.org/10.54099/aijbs.v4i2.949Abstract
The purpose of financial reports is to give people meaningful information about the company's actual state, which helps them make decisions. It's important to be aware that when businesses offer financial reports, they can do so with accuracy and without engaging in dishonest business activities that could mislead consumers into making poor financial decisions. In order to distinguish between financial reports that are suspected of being altered and those that are not, a detection tool is required. The Beneish M-Score Model is a financial statement fraud detection technique used in this study. This study aims to investigate and evaluate the possibility of financial report fraud. The information utilized is secondary data taken from the financial reports of manufacturing companies in the food and beverage subsector that are listed on the Indonesia Stock Exchange (BEI). Utilizing Microsoft Excel and SPSS 26 software, a quantitative approach involving discriminant analysis is employed. Based on independent factors, an item can be divided into two or more categories using the discriminant analysis approach. The results of this research show that the variables that are able to distinguish between samples of financial reports that are suspected to have been manipulated and those that are suspected not to be manipulated are the Days Sales in Receivables Index (DSRI), Gross Margin Index (GMI), Asset Quality Index (AQI) and Sales Growth Index (SGI) variables) is proven to be able to distinguish financial reports that are suspected to have been manipulated. Meanwhile, the Depreciation Index (DEPI), Sales, General and Administrative Expenses Index (SGAI), Leverage Index (LVGI) and Total Accruals to Total Assets (TATA) variables were proven unable to distinguish financial reports that were suspected to have been manipulated.
Keywords
Beneish M-Score Model, Financial Statement Fraud.
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