Use of Data Envelopment Analysis to Measure the Technical Efficiencies of Banks in India

Abstract

Data envelopment analysis (DEA) has been applied in many studies in the banking industry. It is a nonparametric method in Operations Research and Economics for measuring the relative efficiency of peer decision making units (DMUs) that have multiple inputs and outputs. Companies use many different inputs (such as assets, employees, shareholders’ equities, etc.) to generate outputs (such as profits, revenues, market values, etc.). This paper is an attempt to implement the Data Envelopment Analysis (DEA) approach to measure the relative efficiency of a sample of banks in India over a period of one year, Q1-FY 14-15 and Q2-FY 14-15. The authors demonstrate that DEA is an effective tool for monitoring and controlling the performance of banks, which are growing as an important sector in India. The authors followed a case study methodology where data about the inputs and outputs of banks were gathered and analyzed to compute the relative efficiency of the banks. Based on the results obtained, the overall efficiency of the banks studied was about 95.9 and 97.1% respectively. Later, inefficient banks were investigated closely to identify the areas in which the use of resources manifest decreasing returns to scale. The authors concluded the paper with some recommendations on the applicability of the DEA for banks’ efficiency evaluation. Due to the absence of research work, in this discipline, in the banks in India, this study will add to our knowledge on how banks in India may apply DEA to measure their efficiency, and how they might use the results to overcome efficiency problems. Although the results of the present paper are limited to the banks studied, the DEA approach could trigger the attention of policy makers to apply DEA to improve the efficiency of other DMUs.