Evaluating Saudi Banks’ Financial Performance Using an Entropy–TOPSIS Framework

As Saudi Arabia accelerates its Vision 2030 economic diversification, the domestic banking sector serves as the critical engine for capital deployment. However, evaluating these institutions is complicated by conflicting performance indicators, where high profitability is often offset by elevated market valuation multiples. This study applies an objective, established multi-criteria decision-making (MCDM) framework—combining Shannon’s Entropy for objective weighting with TOPSIS for ranking—to evaluate ten major banks listed on the Saudi Stock Exchange (Tadawul), tracked by the Tadawul All Share Index (TASI), over the 2021–2025 period. The contribution is contextual and empirical rather than methodological: the systematic application of established objective MCDM methods to the Saudi banking sector during the pivotal Vision 2030 window, with an investor-oriented criterion set. Comparative validation was executed using the CRITIC weighting algorithm and the VIKOR ranking method, complemented by a four-dimensional sensitivity analysis (Weight Perturbation, Leave-One-Criterion-Out, Alternative Normalization, and Equal-Weight scenarios). Spearman correlation coefficients (>0.86) confirm that the framework produces empirically stable rankings resistant to methodological perturbation, providing policymakers and investors with a data-driven decision-support tool for the Saudi banking sector under Vision 2030.