An Application of Fuzzy Logic to Bank Ranking: A study of the Banking Sector in Bangladesh
Khadijatul Kobra1, Md. Atiqur Rahman2, Syeda Maria Rahman3, Nafees Imran4, Md Faisal Kabir5

1Khadijatul Kobra, Department of General Educational Development, Daffodil International University, Bangladesh.
2Md. Atiqur Rahman, Department of Computer Science and Engineering, Daffodil International University, Bangladesh
3SyedaMaria Rahman, Department of Software Engineering, Daffodil International University, Birulia, Bangladesh.
4Nafees Imran, Department of Information Technology and Management, Daffodil International University, Birulia, Bangladesh.
5Md Faisal Kabir, South Bangla Agriculture, Commerce Bank, Bangladesh.
Manuscript received on 17 October 2022 | Revised Manuscript received on 05 April 2023 | Manuscript Accepted on 15 May 2023 | Manuscript published on 30 May 2023 | PP: 19-26 | Volume-12 Issue-1, May 2023 | Retrieval Number: 100.1/ijrte.D73221111422 | DOI: 10.35940/ijrte.D7322.0512123

Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (

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.
Keywords: Capital Adequacy, Asset Quality, Management Efficiency, Earnings, Liquidity, Sensitivity to Market Risk, Pairwise Comparison Matrix, Fuzzy Geometric Mean, Defuzzification, Fuzzy Weights, FAHP, TOPSIS, Mean, Fuzzy Number.
Scope of the Article: Fuzzy Logic