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1.
SCMS Journal of Indian Management ; 18(4):68-79, 2021.
Article in English | ProQuest Central | ID: covidwho-1762627

ABSTRACT

The present pandemic situation has led to the rise in the number of financially distressed companies in the Indian business ecosystem. Stakeholders, especially shareholders, unsecured and trade creditors who do not enjoy lien on company assets, should be extra cautious about the financial status of a company before making any investment or lending decision. The present study attempts to suggest the key indicators of corporate financial status after analysing 12 ratios from the financial statements of 162 sample companies for five financial years. The suggested key indicators can assist the shareholders and creditors in differentiating a financially distressed company from a financially sound company in the Indian industrial sector.

2.
Vision ; : 09722629211036207, 2021.
Article in English | Sage | ID: covidwho-1390441

ABSTRACT

The unprecedented pandemic COVID-19 has impacted businesses across the globe. A significant jump in the credit default risk is expected. Credit default is an indicator of financial distress experienced by the business. Credit default often leads to bankruptcy filing against the defaulting company. In India, the Insolvency and Bankruptcy Code (IBC) is the law that governs insolvency and bankruptcy. As reported by the Insolvency and Bankruptcy Board of India (IBBI), the number of companies filing for bankruptcy under IBC is on a rise, and the industrial sector has witnessed the maximum number of bankruptcy filings. The present article attempts to develop a credit default prediction model for the Indian industrial sector based on a sample of 164 companies comprising an equal number of defaulting and nondefaulting companies. A total of 120 companies are used as training samples and 44 companies as the testing samples. Binary logistic regression analysis is employed to develop the model. The diagnostic ability of the model is tested using receiver operating characteristic curve, area under the curve and annual accuracy. According to the study, return on assets, current ratio, debt to total assets ratio, sales to working capital ratio and cash flow to total assets ratio is statistically significant in predicting default. The findings of the study have significant implications in lending and investment decisions.

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