Modelscape: Implementing Model Risk Management to Overcome Model Risk Challenges
Watch an introduction to the concept of model risk management and the importance of managing model risk within financial institutions. You’ll learn how models are used in financial decisions, such as mortgage loan approvals, and that the accuracy of these models and the data they use are crucial for making sound decisions. The speaker highlights the potential consequences of using inaccurate models or misapplying them, using a significant financial loss by J.P. Morgan as a case study.
Regulatory measures have evolved to mandate a robust model risk management framework, with regulations in various countries emphasizing the need for clear roles, comprehensive model lifecycle oversight, detailed documentation, and continuous performance monitoring to avoid penalties and reputational damage.
Learn about the “three lines of defense” strategy for effective risk management, which includes the creators and users of models, independent validators, and auditors. Modelscape is a model risk management solution by MathWorks, covering development, validation, testing, deployment, monitoring, and governance. It offers features like a centralized database for model information, enhancing documentation, transparency, and compliance.
Published: 14 Apr 2024
Modelscape. MathWorks model risk management solution. What is model risk? What is model risk management? And what is Modelscape? I am Alex, the product manager for Modelscape, and I will answer these questions in four minutes.
Last year, I applied for a mortgage loan. The bank utilized a model to determine my eligibility for the loan. A model turns input data, such as my credit score and income, into quantitative estimates to make decisions. If the model is not good, the decisions may not be good either. But even a great model can be wrong if it uses incorrect data. Plus, sometimes, a model that seems fine in tests doesn't perform as expected in real situations. It's also crucial to use a model for its intended purpose. For instance, a model designed for pricing home loans isn't suitable for a probability of default model. So it's not just about the model being good or bad.
In 2012, JP Morgan faced a massive financial loss. This loss was linked to errors in the risk models, which didn't properly estimate the risk of some complex financial products. This mistake led to a big financial hit and harmed the bank's reputation. Incidents like these have prompted stricter regulatory measures.
This is a historical overview of how regulations evolved. I can name SR11-7 in the US, OSFI in Canada, SS1/23 in the UK, and was published in 2023. They all mention the need for, and importance of, having a model risk management framework that involves defining clear roles and responsibilities, overseeing a model's entire life cycle, maintaining detailed documentation, and conducting continuous performance monitoring.
Non-compliance with regulations can lead to penalties and damage the reputation. Therefore, having a team dedicated to model risk management is a must. Financial institutions deal with a wide array of products and services, each carrying its risk profile. They operate in a highly-regulated environment, needing to comply with various regulations. The interconnected nature of their operations means that risks in one area can quickly impact others. Hence, the necessity for the three lines of defense arises, establishing a distinct framework of roles and responsibilities for effective risk management.
The first line of defense involves the teams and individuals who directly create, use and manage models. The second line performs independent model validation to assess the accuracy and effectiveness of models. The third line objectively evaluates and reports on the efficiency of the first and second lines in managing risks.
MathWorks' Modelscape solution makes managing financial models easier for banks and financial companies. It helps with every step of a model's life from start to finish, enhancing documentation, transparency and compliance.
It enables users to develop. This is the initial stage where models are created using appropriate data and methodologies. Documentation of development processes is also important for transparency and auditability.
Validate is the ability to validate the models in live environments. Test is the ability to test those in pre-production and to deploy and monitor them. Governance provides a centralized database, or list, that contains detailed information about every model that an organization uses. This includes an inventory, workflows, audit logs, automated notifications, model dependencies, and more.
For more information, you can check the product page, mathworks.com/modelscape.