Performance analysis of Indian private sector banks: insights from CAMELS and statistical technique

https://doi.org/10.55214/25768484.v9i5.7475

Authors

  • Sunil Sharma Department of Management Studies, B S Abdur Rahman Crescent Institute of Science and Technology, Chennai, India.
  • S Prasanna Department of Management Studies, B S Abdur Rahman Crescent Institute of Science and Technology, Chennai, India.
  • Amir Ahmad Dar Department of Statistics, Lovely Professional University, Punjab, India.

The performance of banks is crucial for a country’s economic development as they serve as important financial intermediaries. This study aims to evaluate the performance of private sector banks in India using the CAMELS model. The CAMELS model evaluates bank performance based on six parameters: Capital Adequacy, Asset Quality, Management Quality, Earnings, Liquidity, and Sensitivity to Market Risk. Regression analysis and ANOVA are employed to examine the influence of these CAMELS parameters on banks' return on assets (ROA). Additionally, a weighted average rating technique is used to rank each bank according to the CAMELS parameters. The study utilizes data from 20 banks in the private sector over 24 years from 2000 to 2024 to evaluate these ratios. The study provides insights into the financial health of India’s private sector banks, highlighting the significance of CAMELS parameters in determining bank performance. The results indicate which factors most strongly influence ROA and how banks rank based on their overall financial stability. The research underscores the importance of continuous monitoring of CAMELS parameters to ensure the sustainable performance of banks. The findings serve as a valuable tool for stakeholders, including investors, policymakers, and regulators, by enabling informed decision-making regarding bank performance and stability.

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How to Cite

Sharma, S. ., Prasanna, S. ., & Dar, A. A. . (2025). Performance analysis of Indian private sector banks: insights from CAMELS and statistical technique. Edelweiss Applied Science and Technology, 9(5), 2355–2371. https://doi.org/10.55214/25768484.v9i5.7475

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Published

2025-05-23