An Overview - Stress Test Designs for the Evaluation of AI and ML Models Under Shifting Financial Conditions to Improve the Robustness of Models

Abstract

The dynamic landscape of financial risk management is increasingly influenced by the integration of Artificial Intelligence and Machine Learning models. These advanced computational approaches have shown remarkable proficiency in analyzing complex, voluminous financial data, leading to enhanced predictive accuracy and decision-making in finance. This paper presents a comprehensive overview of evaluating and enhancing the robustness of AI and ML models in finance through advanced stress testing designs. We delve into the methodologies of stress testing AI and ML models, focusing on scenario development, model input variation, and performance metrics. The paper also critically examines regulatory perspectives and compliance with specific focus on Basel Committee guidelines and the integration of stress testing in risk governance. Challenges in regulatory compliance for AI/ML models are analyzed, highlighting the need for balancing predictive performance with regulatory standards. The discussion extends to the effectiveness of current AI/ML stress testing approaches and strategies for enhancing model robustness and reliability. We underscore the implications for policymakers and financial institutions, emphasizing the necessity for adaptive and resilient financial systems. The paper concludes by outlining future research directions, advocating for advancements in AI/ML methodologies and their applications in financial risk management to foster robust, efficient, and transparent financial systems. This study aims to provide valuable insights for academics, practitioners, and policymakers involved in financial risk management and AI/ML application in finance.

Keywords: Artificial Intelligence, Machine Learning, Financial Risk Management, Stress Testing, Model Robustness, Regulatory Compliance, Basel Committee Guidelines, Predictive Analytics, Financial Stability, Risk Governance

JEL Classification: G00