Beneish Model for Financial Report Fraud Identification in the Manufacturing Sector During the COVID-19 Pandemic - Yanuar Ramadhan; Novera Kristianti Maharani; Ernawan Dwi Hanartyo (AIBPM Publisher, 2026)
Financial statement fraud misleads stakeholders’ judgments and erodes market confidence in corporate transparency, and this risk is particularly prominent during the period of high economic uncertainty brought by the COVID-19 pandemic. This study targets basic and chemical manufacturing companies listed on the Indonesia Stock Exchange (IDX), adopts the Beneish M-Score model, and focuses on the window period before and after the COVID-19 outbreak, aiming to analyze the impact of four categories of financial ratios—liquidity, solvency, profitability, and operating capacity—on fraud detection. The study adopts a quantitative explanatory design and processes data through panel data regression and the EViews software. Its sample consists of relevant data from 60 companies covering the period 2019–2022, totaling 240 firm-year observations. The empirical results show that liquidity (b=0.214, p=0.0001) and profitability (b=0.038, p=0.0000) have a significant positive impact, while solvency (b=-0.013, p=0.7128) and operating capacity (b=1.005, p=0.0596) have no significant impact; 89% of the annual reports have no likelihood of manipulation, and 11% carry potential manipulation. The conclusions can assist various stakeholders, including investors and regulators, in identifying early warning signals of fraud.