Artificial intelligence risk management framework in Financial and Banking Organizations: Proposed model and approach

Abstract

Artificial Intelligence (AI) is playing an increasingly important role in the financial and banking sector, but also raises multiple challenges related to transparency, fairness, explainability, and regulatory compliance. This study proposes an AI risk management framework specifically designed for financial institutions, grounded in the integration of the KAIRI index (Knowledge, Accuracy, Interpretability, Robustness, Impact) with established AI risk management frameworks. The framework is intended to facilitate the identification, quantification, and mitigation of risks across the entire operational lifecycle of AI systems. Its development is informed by a synthesis of domestic and international research, and it is structured around five foundational pillars: transparent design, quantitative risk assessment, lifecycle monitoring, independent auditing, and compliance–ethics. By leveraging KAIRI as a core foundation in conjunction with existing frameworks, this approach provides a comprehensive and practicable pathway for the safe, sustainable, and governance-aligned adoption of AI within financial institutions.