An Application of Fuzzy Logic to Bank Ranking: A study of the Banking Sector in Bangladesh

Abstract

Creditors, investors, policymakers, and other stakeholders are all significantly impacted by banks’ performance ratings since these ratings affect how well banks are able to compete in the banking industry, which is crucial for the growth of this industry. The criteria used to evaluate a bank’s success in the banking industry are nebulous and vague. Consequently, it is no longer possible to precisely determine the state of a bank using the analytical method. Furthermore, there is no standard framework that can evaluate private commercial banks using the CAMELS criterion and eliminates ambiguity that we can witness in Bangladesh. The literature shows that two multi-criteria decision-making procedures, FAHP and TOPSIS, are employed in many countries to rank banks according to the CAMELS criteria. However, in Bangladeshi private commercial banks, we have never used such models using the CAMELS criteria. In order to assess the performance of Bangladeshi private commercial banks, this study aims to propose a Fuzzy Multi-Criteria Decision Model (FCDM) that can handle uncertain and ambiguous data. The CAMELS (Capital Adequacy, Asset Quality, Management Efficiency, Earnings, Liquidity, and Sensitivity to Market Risk) criteria are used to analyze and rank the ten commercial banks in Bangladesh. The suggested model incorporates the Fuzzy Analytic Hierarchy Process (FAHP) and Technique of Order Performance by Similarity to Ideal Solution (TOPSIS) methodologies. The weights are input into the TOPSIS algorithm to rank the Banks after determining the weight vector of the CAMELS criteria based on the opinions of experts using FAHP. The outcome displays the ten Bangladeshi commercial banks’ final rankings.