An Integrated Fuzzy AHP and Fuzzy TOPSIS Approach for Ranking and Selecting the Chief Inspectors Of Bank: A Case Study

Abstract

Nowadays selecting the best inspectors has triggered a substantially significant issue among today's competitive environment, in particular some prominent banks. It's because the efficient supervision of banking activities is necessary for both achieving a powerful economic environment and financial stability of the country, Chief inspectors as highest position of the banks play an important role. Additionally, the bank inspectors are in charge of supervising bank activities to ensure that there is sufficient capital and reserves to deal with risks when they encounter to critical situations. On the other hand, although the banking supervision costs is really high, but the poor monitoring can bring about higher costs. So, this paper presents a hybrid method of fuzzy AHP and Fuzzy TOPSIS to select the best chief inspector of banks based on some various qualitative and quantitative criteria with different priorities. The Fuzzy AHP and TOPSIS methods are used to determine the weight importance of criteria and ranking the selected inspectors, respectively. The proposed method was applied to a real case study on one of the most prominent Banks of Iran country and the obtained results show that our proposed method is so practical to make the best decision of selecting the bank chief inspectors.