Total views : 295

Multivariate Bank Performance Analysis using Standardized CAMEL Methodology and Fuzzy Analytical Hierarchical Process


  • Department of Management Studies, National Institute of Technology, Silchar – 788010, Assam, India


Objective: To minimise the subjectivity of the CAMEL approach by applying FAHP for ranking the banks playing an important role in Indian financial system and also aims to help the investors to make informed decisions. Methods/Statistical Analysis: Banks listed in the CNX bank Index and National Stock Exchange are selected for the validating the model. The trading frequency of about 90 percent for the last six months and positive net worth are additional criteria imposed for the purpose. FAHP is used to assign weights to the main and Sub criteria designed for the purpose of ranking of the banks. TFN is used for the verbal judgements and the criteria weights are assigned to the CAMEL ratios and the final scores are calculated. Findings: CAMEL finds its worldwide applicability in measuring the performance of the banks but on subjective way. It is needed to provide objectivity in the subjective judgment to eliminate confusion. The FAHP approach is used to assign weights to the CAMEL parameters to judge the ranking positions of the Indian banks for the purpose. Use of FAHP in CAMEL ratios is a unique work which will help to rank the banks according to their performance and help to make informed decisions. As per the findings it is revealed that, in Indian financial system SBI's performance is highest and Central Bank's performance is lowest. The present work will complement the effort of the policy makers and general investors to understand the performance of the banks in the Indian financial system through an objective approach to the subjective judgmental process. Application/ Improvements: The study mainly concentrated on developing a bank rating model with the use of Fuzzy Logic for effective rating of the banks in India. The present scope can be extended to include larger data sets and diverse economic conditions.


Bank Rating, CAMEL, FAHP, Multivariate Bank Performance Analysis.

Full Text:

 |  (PDF views: 245)


  • Banking India updates. Available from http://bankingindiaupdate. com/bankrating.html. Accessed on 05/01/2016.
  • Portable document format.file:///F:/Personal%20papers/ CAMEL%20&%20FAHP/GIRAFE%20rating.pdf. Accessed on 15/06/2016.
  • Dash M, Das A. A CAMELS Analysis of the Indian Banking Industry, Social Science Research Network paper no. 1666900. Available from Accessed on 15/07/2016.
  • Podpiera ADJ. Predicting Bank CAMELS and S&P Ratings: The Case of the Czech Republic, Working paper series, Czech National Bank. 2004.
  • Reddy SK. Relative Performance of Commercial Banks in India Usinf CAMEL Approach. ZENITH International Journal of Multidisciplinary Research. 2012; 2(3):1–21.
  • Sandhya Ch VL. Camel Framework in Banks - Indian Scenario. Indian Journal of Applied research. 2014; 4(6):1– 3. CrossRef.
  • Dang U. The CAMEL Rating System in Banking Supervision A Case Study. Arcada University of Applied Sciences International Business. 2011; 1–47.
  • Mamun MAA. Performance Evaluation of Prime Bank Limited in Terms of Capital Adequacy. Global Journal of Management and Business Research Finance. 2013; 13(9):1–5.
  • Misra SK, Aspal PK. A Camel Model Analysis of State Bank Group. World Journal of Social Sciences. 2013; 3(4):36–55.
  • Hays FH, Lurgio SD A, Jr.Gilbert AH. Efficiency Ratios and Community Bank Performance. Journal of Finance and Accountancy. 2009 Aug; 1:1.
  • Weakness-banks. Accessed on 06/03/2016.
  • Madura J. Financial Institutions and Markets, South Western College. 2010.
  • Tunay KB, Akhisar I. Performance Evaluation and Ranking of Turkish Private Banks Using AHP and TOPSIS. Management International Conference, 2015 May. p. 1–8.
  • Chaterjee D, Chowdhury S, Mukherjee B. Application of Fuzzy Analytical Hierachical Process (FAHP) in the Ranking of Indian Banks. International Journal of Engineering Science and Technology. 2010; 2(7):2511–20.
  • Gupta R. An Analysis of Indian Public Sector Banks Using Camel Approach. IOSR Journal of Business and Management (IOSR-JBM). 2014; 16(1):94–102. CrossRef.
  • Arbel A, Orger YE. An application of AHP to bank strategic planning: the merger and acquisitions process. European Journal of Operational Research. 1990; 48(1):27–37. CrossRef.
  • Vaidya OS, Kumar S. Analytic hierarchy process: An overview of applications. European Journal of Operational Research. 2006; 169:1–29. CrossRef.
  • Akkoc S, Vatansever K. Fuzzy Performance Evaluation with AHP and Topsis Methods: Evidence from Turkish Banking Sector after the Global Financial Crisis. Eurasian Journal of Business and Economics. 2013; 6(11):53–74.
  • Bernè F, Mattia C, Maurizio F, Daria M, Pediroda V. Multi Criteria Credit Rating (MCCR): A Credit Rating Assignment Process for Italian Enterprises According to Basel II. Proceedings of MCDM 2006, Chania, Greece: 2006 Jun. p. 19–23.
  • Domański CZ, Kondrasiuk J. Analytic Hierarchy Process - Applications in Banking. Innovations in Classification, Data Science, and Information Systems. Springer; 2005. p. 616.
  • Hunjak T, Jakovcevic D. AHP Based Model for Bank Performance Evaluation Nad Rating, ISAHP. Berne, Switzerland: 2001 Aug. p. 1–10.
  • Voutilainen PKLKR. Finding the Most Preferred Alliance Structure between Banks and Insurance Companies, Helsinki School of Economics, Working Papers, 2004. p. 1–23.
  • Chen-Yu L, Cheng, Jao-Hong. A fuzzy AHP application on evaluation of high-yield bond investment. WSEAS Transaction on Information Science and Applications. 2008; 5(6):1044–56.
  • Macerinskiene I, Ivaskeviciute L, Babarskas J. Multiple Criteria in Bank Loan Portfolio Management. Ekonomika. 2004; 67:1258–392.
  • Trifonova S, Zlateva P. A Fuzzy Logic Model for Estimation of Banking System Stability in Bulgaria. 2017. p. 46–50.
  • Moon TH, Lee WB. Construction Of Supporting System For Decision Making Process Of Zoning Designation and Change That has Fuzziness. The 6th International Conference Computers in Urban Planning and Urban Management, 1999. p. 1–7.
  • Saaty TL. The Analytical Hierarchy Process. New York: Mc Graw Hill; 1980. p. 1–12.
  • Chiara mocenni. Available from Accessed on 15/07/2016.
  • Nang-Fei P. Fuzzy-AHP approach for selection of bridge construction method. Automaton in construction. 2008; 17:958–65. CrossRef.
  • Buckley JJ. Ranking Alternatives Using Fuzzy Members. Fuzzy Sets and Systems. 1985; 15:21–31. CrossRef.
  • Mehdi F. The fuzzy evaluation of E-Commerce customer satisfaction. World appl sc journal. 2008; 4(2):164–8.


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.