Financial Distress and Earnings Manipulation in India’s Nifty Metal Sector: A Forensic Accounting Assessment

Financial distress and earnings manipulation are widely linked by theories, but are rarely analyzed jointly with firm-level control variables in emerging markets. This study analyses the relationship among 14 firms in the Nifty metal sector listed on the NSE from FY2016 to FY2025, applying Altman’s Z-score and Beneish’s M-score models to 122 firm-year observations. The results show widespread distress during COVID-19, while signs of earnings manipulation were episodic. Pooled ordinary least squares regression indicates no significant association (β = 0.004, p = .733), while Spearman correlation (β = 0.243, p = .007) and Ramsey RESET result ( p = .003) indicate the association is real but non-linear. Sales growth and current ratio emerge as strong predictors of earnings manipulation and remain robust when removing the pandemic period. By collectively applying both forensic models with firm-level control variables to an under-inspected, high-leverage Indian sector, the study contributes to the forensic accounting literature on the distress–manipulation nexus and supports evidence-based accountability and corporate transparency. Findings provide valuable insights for auditors and regulators, including firm-characteristics-based red flags beyond the distress score alone. Limited to one sector and an accrual-based measurement, the study points to future research towards non-linear specification and measurement of real-activity manipulation.