Application of Multi-Criteria Decision Making Models in Regulatory Evaluation of Commercial Banks in India and its Consistency with Public Perception

This paper, first, examines the performance of a sample set of public sector banks (nationalized banks and State Bank of India) and a sample set of private sector banks in terms of certain regulatory variables. It uses aggregation techniques like TOPSIS, VIKOR and ELECTRE - III to rank their performance. This exercise is done over a period of time to see whether the ranking of banks, both in the private sector and the public sector, has undergone any change. These aggregation techniques provide an alternative method to that of CAMELS used by Reserve Bank of India. Second, the paper delves into market perception of these two sets of banks and ranks them in terms of the aggregation techniques. The paper then combines the above two approaches to check whether the market at large understands the regulatory framework that the banks need to follow. Variables like RISK (Risk Weighted Assets/Total Assets), CAR (Actual Capital Adequacy Ratio), CRRISK (Provisions/Total Advances), VULNER (Ratio of Deposits to Risk Weighted Assets), CLSTATE (Ratio of Government Security Holdings to Total Assets), ROA (Returns on Assets), Net Interest Margin and NPA percentage are selected to represent regulatory variables. Price/Earnings (P/E) Ratio, Price/Book Value per Share (P/BVPS), Size as measured by size of deposits, Dividend Payout Ratio, Dividend Yield and ROE are chosen to represent public perception banks