A hybrid framework for assessing Pakistani commercial bank performance using multi-criteria decision-making

Overall bank performance in a particular year or period is important to all banking industry stakeholders, as it indicates their success or failure relative to predetermined targets. Due to conflicting criteria and uncertainties, assessing bank performance is a complicated decision-making problem. The current paper proposes the Fuzzy Level Based Weight Assessment (F-LBWA), the Fuzzy Logarithm Methodology of Additive Weights (F-LMAW), and the Measurement Alternatives and Ranking according to the Compromise Solution (MARCOS) combination as a practical and robust decision-making tool to cope with many complex ambiguities. In the first phase, the suggested hybrid Multi-Criteria Decision-Making (MCDM) approach estimates the weight coefficients of the performance criteria with the aid of a combined version of the F-LBWA and F-LMAW methods. In the second phase, the MARCOS method determines the ranking performance of the decision alternatives. The introduced model is tested and validated on a case study assessing publicly traded bank performance in Pakistan. The findings obtained from the sensitivity analysis revealed that the presented F-LBWA-F-LMAW-MARCOS approach produces consistent solutions and is a reliable and effective procedure in rational decision-making.