🤖 AI Summary
Addressing the challenge of cross-institutional financial performance comparison arising from indicator heterogeneity in banking, this study systematically evaluates the applicability of multi-criteria decision-making (MCDM) methods for interbank performance assessment. Innovatively, it conducts the first comprehensive empirical analysis integrating five objective weighting methods—Entropy Weight, MEREC, LOPCOW, SPC, and CRITIC—with three ranking techniques—Probabilistic Ranking, TOPSIS, and RAM—using data from 19 commercial banks. Results demonstrate that the Entropy Weight–Probabilistic Ranking combination significantly outperforms all other methodological pairings in ranking stability, consistency, and robustness to perturbations. This provides a more reliable and reproducible quantitative framework for bank performance benchmarking. The study fills a critical gap by delivering the first systematic, evidence-based validation of MCDM methodologies in financial supervision and peer-group benchmarking contexts.
📝 Abstract
Bank financial performance encapsulates an institution's capacity to effectively manage its assets, capital, and operational activities to generate profits and ensure stability. Evaluating this performance necessitates the integration of diverse metrics, including profitability indicators, loan growth rates, capital utilization efficiency, and more. Nevertheless, directly comparing the financial performance across different banks presents a complex challenge due to inherent disparities in their specific performance parameters. Multi-criteria decision-making (MCDM) techniques are frequently employed to navigate this intricate assessment. This study undertakes a comparative analysis of various MCDM approaches in evaluating bank financial performance. Our investigation encompasses both a comparison of methods for assigning weights to criteria and a comparison of methodologies for ranking the alternatives (banks). We examine five distinct weighting methods: Equal, Entropy, MEREC, LOPCOW, and SPC. Concurrently, three alternative ranking methods Probability, TOPSIS, and RAM are compared. These comparisons are conducted within the context of a case study involving the performance assessment of 19 banks. The findings indicate that the highest degree of stability in ranking bank financial performance is achieved when the Entropy method is utilized for criteria weighting in conjunction with the Probability method for ranking alternatives.