Back in school, cramming for an exam may have been acceptable (although stressful). But it’s never the best option for lenders preparing for their next regulatory “exam” on model risk management. Fortunately, there’s no need to cram for an audit if you adopt good model management practices from the get-go.
Your preparation must begin well ahead of an audit, a point made clear by the 2011 Supervisory Guidance on Model Risk Management issued by the US Office of the Comptroller of Currency (OCC) and similar guidance in the Federal Reserve’s SR 11-7. These guidelines require sound and robust processes for model development, validation, implementation, use and governance. This has always been good policy, but in the regulatory climate following the post-financial meltdown, it becomes even more critical.
How can you make sure you’re prepared? Here are a few tips:
Understand the scoring models you use, both those developed in-house as well as those from third-party vendors. The guidelines state that bankers must demonstrate a clear understanding of the model’s capabilities, applicability, and limitations and oversight of the models that drive their credit decisions.
Ensure the model is used for its intended purpose. A model developed on one product type shouldn’t be deployed for another type without first conducting a proper validation to ensure it works for that product type, too.
Maintain good documentation.
- Be prepared to show reports, such as for application approvals, overrides and delinquencies.
- Show that you follow established processes for model management, from development to implementation, as well as processes for model use, ongoing monitoring and validations.
- Show empirical evidence that each model is predictive. Maintain ongoing evidence showing the models are implemented in the environment for which they were built and remain predictive as designed.
Validate the tools you use, particularly the models. Validations should assess the quality of the model design and construction, provide ongoing monitoring that the model is performing as intended, and compare the actual outcomes to the predicted/expected results.
Manage score overrides. If there is an override policy in place, follow it. Don’t allow subjective override decisions.
Limit ad hoc adjustments to models. Models must be empirically derived, demonstrably and statistically sound (EDDSS). Even minor “unempirical” adjustments to a model may jeopardize EDDSS status and could raise potential fair lending compliance concerns from examiners related to Regulation B of the Equal Credit Opportunity Act.
Monitor the scoring models. Track your portfolio using standard reporting (e.g., population stability or characteristic analysis). Conduct periodic model evaluations to demonstrate that it continues to rank-order risk effectively.
Need extra credit? You'll find more tips in our Insights white paper, "Comply and Compete: Model Management Best Practices" (No 55, requires registration to download).