Efficiency measurement in the banking sector with data envelopment analysis

Financial development is the basis of the development level of countries. The financial development depends on creating, distributing, and using existing funds where necessary. Since these funds are mediated by the banking sector today, the performance of the banking sector is of great importance in terms of the growth, development, and effective functioning of both national economies and international economic systems. For such an important sector, it is inevitable to conduct an efficiency analysis. Efficiency can be defined as the relationship between the existing resource capacity of firms and the active portion of this resource capacity. Although there are many methods and techniques used in the banking sector for efficiency measurement, data envelopment analysis is a method that measures the effectiveness of decision-making units operating in the same field and using similar input and output variables and allows them to be ranked. The data obtained using data envelopment analysis provides an idea about how effective a certain decision-making unit is, which variable should be changed to what extent, and in what direction for an ineffective decision-making unit to be effective. In the first chapter of the study, the measurement of efficiency and measurement methods were explained. In the second chapter, data envelopment analysis was interpreted, and studies and models that contributed to the literature were defined. In the third chapter, the Turkish banking sector and the application of 11 banks operating in Turkey between 2018 - 2020 were analyzed. The data analysis report of the data envelopment analysis applied in the Frontier Analyst package program and the results of the study were included in the third chapter. This study uses interest and non-interest expenses as inputs, loans, and interest and non-interest income as outputs by considering mediation and profit approaches. The constant returns to scale model, one of the data envelopment analysis models, was applied in the application area. In conclusion, although some banks' efficiency values were lower than one in the CCR model since these values are found very close to one, they can be evaluated as effective. Again, although the super-efficiency values are different, it has been determined that there is no significant difference in the efficiency level of the banks. According to the CCR model in the study, 8 of the 11 banks were found to be effective in 2018, 9 in 2019, and 6 in 2020. It can be said that banks carry out their activities at sector averages. Banks whose efficiency value is less than one (but very close to one) need to increase the amount of output they get in their activities to be effective. However, this result may differ according to the selected variables. In order to find the reason for the relative inefficiency of banks, investigations can be made by using different variables, that is, by including different inputs and outputs in the analysis.