Benchmarking the private sector banks in India using MCDM approach

Abstract

The study aims to rank the performance of Indian private sector banks on the basis of their financial capability. The study is focussed on those banks which are listed in the Bombay Stock Exchange (BSE), for the period from 2014–15 to 2018–19. The financial performance of selected Indian private banks is ranked using a hybrid Multi‐Criteria Decision Making (MCDM) technique, that is, AHP‐TOPSIS. The Analytical Hierarchy Process (AHP) is used to determine the weights of 10 financial performance pointers, and further Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to provide rankings and benchmarking of the private sector banks. Thereafter, overall ranking is given to the selected banks using interval‐valued TOPSIS (IV‐TOPSIS) for a combined period of 5 years. Sensitivity analysis has been performed to check the robustness of the method and its impact on the final ranking of the banks. Results showed that HDFC bank is the top performer and is ranked first for all the years consecutively during the period 2014–2019 and has set a financial indicator benchmark for other competitor banks. South Indian Bank showed the worst results in each year and stood last in the overall ranking. The IndusInd bank is followed after HDFC bank by improving its performance from 2014–19. With a slight margin, Kotak Mahindra Bank ranked after IndusInd. Through the AHP‐TOPSIS technique, each year the private sector banks ranking differs among themselves depending upon the financial performance pointers. Based on interval‐valued TOPSIS (IV‐TOPSIS), it was found that the overall HDFC was the top‐performing bank and South Indian Bank was the worst‐performing bank among all other banks. The results obtained from sensitivity analysis were found to be consistent with IV‐TOPSIS. The paper used the AHP technique, which is subjective in nature, and the results depend on the opinion of the experts. This study will assist the investors who want to channelize their funds in private banks having shares enlisted in BSE. It will accommodate banks to compare and judge their financial performance along with improving their performance and planning their future strategy. AHP‐TOPSIS utilized by past researchers is unable to bring out the cumulative performance for banks, but in this paper, IV‐TOPSIS is utilized, which can be effectively used to evaluate the cumulative performance of banks. The study tries to fill the gap in the literature by providing the overall ranking to private sector banks in India on the basis of financial indicators.

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Stock portfolio selection using a new decision-making approach based on the integration of fuzzy CoCoSo with Heronian mean operator

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Financial Performance Analysis of NBFC-MFIs in India using TOPSIS and IV-TOPSIS

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“…The study has been checked for robustness through sensitivity analysis (Gupta et al, 2020). The analysis is done by altering the criteria weights in 5 sets and ranking the alternatives (NBFC-MFIs) with the altered weights.…”