The purpose of this paper is to empirically assess the efficiency (transaction efficiency, intermediation efficiency and profit efficiency) of the retail branches of a large bank and identify the driver parameters of the same.
The authors use the non-parametric data envelopment analysis approach to analyze the financial performance of 247 branches in 2014, spread over 14 states of a country. After checking for possible misspecification bias, the authors use the fractional regression approach in the second stage of the analysis to assess possible drivers of the efficiency of bank branches in terms of the size of business, funding mix, per employee contribution to business and profit and business per transaction. In addition, the authors included spatial parameters like economic condition and competitive position of branches in their analysis.
The authors find that on an overall basis, there might be a deliberate initiative of the top management of the bank to over-branch in order to improve the output at the aggregate level which is above the level of cost minimization. The study clearly indicates to the top management that low-cost deposit is a significant driver of branch efficiency apart from business per transaction, income per employee. Moreover, it is found that branches located in areas of high branch concentration are more efficient, and local economic condition does drive efficiency of branches.
The authors address the dilemma faced by the top management of banks in arriving at an appropriate scientific benchmark to assess the performance of branches based on the drivers of efficiency and initiate suitable strategic interventions to improve their efficiency.
The integrated assessment of the efficiency of bank branches and arriving at the drivers of efficiency using the fractional regression model framework are likely to prove beneficial in the benchmarking exercise of the performance of bank branches.
Saha, A., Hock-Eam, L. and Yeok, S. (2018), "Deciphering drivers of efficiency of bank branches", International Journal of Emerging Markets, Vol. 13 No. 2, pp. 391-409. https://doi.org/10.1108/IJoEM-11-2016-0301Download as .RIS
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