Designing a Banking Supervision Model Using Performance, Risk, Sustainability (ESG), and Geographical Justice Indicators Based on Game Theory and Graph Modeling
Keywords:
Central Bank, Islamic Banking, Smart Dashboard, APH, Theoretical FoundationsAbstract
The objective of this study is to develop an intelligent and comprehensive banking supervision model integrating performance, risk, sustainability, and geographical justice indicators using game theory and graph analysis to enhance central bank supervisory effectiveness and financial system stability. This applied developmental research adopts a mixed-method (qualitative–quantitative) design. In the qualitative phase, supervisory indicators were identified through literature review, document analysis, and semi-structured expert interviews involving banking executives, financial technology specialists, and decision-science scholars selected through purposive sampling. A fuzzy Delphi method was used to finalize indicators. In the quantitative phase, indicator weights were determined using Analytic Hierarchy Process (AHP) and Best–Worst Method (BWM). Network relationships among indicators were examined using graph modeling and network analysis software. Strategic responses of banks under different regulatory scenarios were simulated through game-theoretical modeling and policy simulations. Results indicate that financial performance, financial health, and systemic risk dimensions hold the highest supervisory priority. Profitability indicators, particularly Return on Equity (ROE) and Return on Assets (ROA), emerged as dominant determinants of banking stability. Credit concentration and interbank dependency were identified as core systemic risk drivers. Graph analysis revealed systemic risk and financial performance as central nodes exerting strong spillover effects across the supervisory network. Game-theory simulations demonstrated that stricter supervisory environments reduce risk-taking behavior and increase operational transparency among banks. Incorporating ESG and geographical justice indicators enhanced the model’s ability to evaluate long-term sustainability and balanced regional financial development. The proposed model provides an integrated and innovative framework for intelligent central bank supervision by combining financial, risk, sustainability, and regional equity dimensions. The framework enables simultaneous performance monitoring, strategic behavior prediction, and identification of critical systemic vulnerabilities, thereby supporting evidence-based policymaking, strengthening financial governance, reducing systemic risk exposure, and promoting equitable banking development.
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