The institution of the Insolvency and Bankruptcy Board of India (IBBI) in 2016 resulted in over 7,000 companies initiating the Corporate Insolvency and Resolution Process (CIRPs), with approximately 15% adopting resolution plans and 45% undergoing liquidation. The rise in CIRP filings, along with a growing number of non-performing loans, strongly indicates the prevalence of financial distress. Bankruptcy prediction models have been consistently attempting to mitigate the consequences of distress by providing early warning signs. Despite a host of research and varied models to predict distress, there is a lot of uncertainty and inconclusiveness as most models are sensitive to time, industry, and the country's financial and economic situations. Further, studies identifying signals about a distressed firm's deteriorating condition over time are rare, with subjective definitions of distress. Therefore, the first objective of this study is to identify financial distress signals and their impact using a hybrid model by combining variables from accounting, market, and reporting anomalies.

In addition to identifiable variables, one of the primary reasons for the collapse of behemoth corporations is deficiencies in internal corporate governance. Conflicts arising out of the separation of ownership and management are often addressed with an efficient internal corporate governance mechanism. Hence, the second objective is to investigate the impact of internal corporate governance quality on financial distress. Given the lack of internal corporate governance quality and poor financial health, distressed firms also have strong incentives to engage in earnings management to conceal their deteriorating condition. Stakeholders rely on published financial statements to evaluate firm performance and future prospects. However, earnings management is usually hidden, leading to significant errors in stakeholders' decision-making. Therefore, the third objective is to explore the extent of earnings management adopted by distressed companies and examine other determinants driving earnings management.

The findings indicate that return on assets, asset turnover ratio, debt-to-equity ratio, market capitalization, and market value of equity to book value of debt serve as credible signals of impending distress. Further, the efficiency of reporting anomalies as a signal depends on the firm's position in the distress continuum. Evidence also suggests that combining accounting, market, and reporting anomaly variables can significantly enhance model accuracy. Findings reveal that financially distressed firms are associated with poor internal corporate governance quality. Further, distressed firms tend to engage in earnings management through real earnings management, primarily via sales manipulations and overproduction. Earnings management is prevalent prior to new debt issuance but not before new equity issuance, and the presence of institutional investors effectively constrains earnings management. Additionally, companies resort to real earnings management when accrual earnings management is restricted by regulation and accounting flexibility.