Designing robust model for banks benchmarking based on Rembrandt method and DEA

Purpose The purpose of this paper is to find excellent banks on the basis of identified variables. First of all, banks are evaluated based on operation costs, deposits, staff, investments, net profit, and loans variables. Subsequently, these variables are categorized into inputs and outputs. The performances of the banks based on these variables are analyzed by data envelopment analysis (DEA) method to find efficiency and inefficiency of decision making units (DMUs). Design/methodology/approach This research is aimed to determine the best banks based on predetermined indicators. The indicators are categorized into inputs and outputs. DEA method is used to find efficiency and inefficiency of DMU. However, the aim is to find the efficient banks and to implement the model by using AP Super Efficiency method in order to find the most efficient unit for benchmarking. However, some inputs and outputs have more priority for banks than the others, as a result it will require some changes. Findings The results indicate that among 13 banks, including ten public and three private, solely five public banks are efficient. Moreover, DEA is used as a benchmarking tool for inefficient banks to be efficient. Among these banks ten of them are public banks and three are private. Among efficient ones, all are public banks. Moreover, five of public banks and three of private are inefficient. Originality/value In some cases, inputs and outputs have more priority for DMs than the others, as a result it will require some changes. Also, if one of the inputs or outputs is larger in number than the others, the DMU becomes efficient, despite its low priority. Thus, for solving this problem, the indicators of this research are ranked by Rembrandt method considering the existing ones to find the best banks (best DMU) based on their performance and the relevant indicators.