Artificial Intelligence Mathematical Decision Framework for Banking Innovation: From AI Prediction to Optimized and Responsible Decisions

Artificial Intelligence-Mathematical Decision Framework for Banking Innovation introduces AIM-DF, an interdisciplinary decision-support architecture designed to bridge the gap between artificial intelligence prediction and managerial decision-making in banking. The framework integrates organizational readiness, AI capability, a Mathematical Decision Engine (MDE), Responsible AI Governance, banking innovation, and organizational outcomes. Rather than treating AI predictions as final decisions, AIM-DF converts predictive outputs into constrained, multi-objective decision problems that account for profitability, operational efficiency, customer value, risk, capital, liquidity, regulatory requirements, and governance. A proof-of-concept empirical demonstration using banking data from Bangladesh illustrates how financial indicators can define decision states within the framework. The book emphasizes that intelligent banking requires not only predictive accuracy but also mathematical optimization, explainability, accountability, human oversight, and regulatory compliance. Combining Finance and Banking, Artificial Intelligence, and Mathematics, AIM-DF provides a foundation for developing transparent, responsible, and evidence-based intelligent financial decision systems, particularly in emerging economies.