ANALYSIS OF FRAUD-DETECTING FINANCIAL REPORTING USING THE M BENEISH SCORE METHOD IN TRANSPORTATION AND LOGISTICS COMPANIES ON THE INDONESIA STOCK EXCHANGE IN 2014-2023

Abstract

The purpose of this study is to use the Beneish M-Score model to detect, evaluate, and test financial statement fraud. The financial statements of 37 companies in the transportation and logistics sector listed on the Indonesia Stock Exchange between 2014 and 2023 served as the secondary data source for this study. Purposive sampling was used in conjunction with a quantitative strategy to select data. The Beneish M-Score model, which consists of eight variables Days Sales in Receivables Index (DSRI), Leverage Index (LVGI), Asset Quality Index (AQI), Sales Growth Index (SGI), Depreciation Index (DEPI), Sales, General, and Administrative Expense (SGAI), and Total Accrual to Total Assets Index (TATA) was used to conduct the analysis and calculate indices, as well as linear regression using eViews12. With this analysis, it can be found differences between samples that have been manipulated, the possibility of manipulation, and not manipulated and find out whether the ratios used have an effect or not. The results of this study are in the 2014-2023 period 42% of companies detected manipulators and 58% classified as non-manipulators, and there are no companies classified as grey companies according to Beneish M-Score. According to eViews12 processing, the 8 ratio variables used support the Beneish M-Score.