What is Model Risk Management?

Model risk management refers to the supervision of risks from the potential adverse consequences of decisions based on incorrect or misused models. The aim of model risk management is to employ techniques and practices that will identify, measure and mitigate model risks i.e. the possibility of model error or wrongful model usage. In financial services, model risk is the risk of loss resulting from using insufficiently accurate models to make decisions, frequently in the context of valuing financial securities, and becoming prevalent in activities such as assigning consumer credit scores, real-time probability prediction of fraudulent credit card transactions, and money-laundering.  Financial institutions are highly reliant on credit, market, and behavioral models for model risk has become a core component of risk management and operational efficiency. These institutions primarily make money by taking risks -  they maximize models to evaluate risks, understand customer behavior, assess capital adequacy for compliance, make investment decisions, and manage data analytics. Implementing an effective model risk management framework is a requisite for organizations that are heavily reliant on quantitative models for operations and decision-making.

Additional Resources

• Smarter risk and compliance with data and AI
• Modernizing risk management
• How to modernize and scale VaR calculations and risk management with Apache Spark, Delta Lake and MLflow Blog
• How to build: A modern risk management solution in financial services