In the fast-changing world of financial markets, the use of quantitative models has become essential for decision-making, risk management, and strategic planning. These models range from traditional frameworks, such as the Black-Scholes option pricing model, to advanced machine learning (ML) algorithms. Their purpose is to capture the complexities of financial instruments and market behavior. However, using these models carries risks. Model risk—the possibility of negative consequences resulting from decisions based on inaccurate or flawed models—has become a significant concern for financial institutions, regulators, and stakeholders.