The 4-Step Plan to Building a Proactive Model Monitoring Program

The 4-Step Plan to Building a Proactive Model Monitoring Program (OMMP)

Ongoing monitoring of financial models – is a core element of the risk management process and could make the critical difference between a gain or loss for your institution. Get it right and you lay the foundation for steady and healthy growth. On the other hand, poor model monitoring could spell massive losses… and is doubly risky because model monitoring is mandated by supervisory guidance on model risk management.

Due to today’s reliance on financial models, “it is now, more than ever, essential to be performing ongoing monitoring of your models for appropriate fit and accuracy,” says Chris Mills, Managing Director here at MVRA.

The number of models is increasing annually by 10-25%, according to McKinsey and Company, and these models need to be monitored more closely than ever during these unprecedented times.

In recent years, some global banks have been caught out, suffering millions of dollars in fines due to poor monitoring of their model risk frameworks. Creating a proactive plan is protection for your institution as much as it is investing in growth. 

So how can you avoid losses and keep your model risk management valid and up-to-date? Here are four steps to creating a proactive Ongoing Model Monitoring (OMM) plan that can help you make the best decision for your OMM framework:

4-Step Proactive Ongoing Model Monitoring Program (OMM)

1. Model Validation

Immediately after implementing a model, perform a pre-production validation check in order to ensure that the model is conceptually sound.

During production, it is important to carry out regular checks on the model’s validity – at least annually – to challenge process verification and outcomes analysis. How often you continue to carry out model validations often depends on your model risk classification (whether it is low/medium/high). 

Bear in mind that model validations need to be kept separate and independent of development. Model aspects such as simplifying assumptions, methodology “shortcuts” and input data need to be critically challenged, in particular.

2. Performance Testing

In addition to validation, the institution should carry out periodic analyses; including benchmarking, sensitivity analysis, scenario analysis, and outcomes testing. In outcomes analysis, it’s advisable to look at back-testing, in-sample testing, and variable testing to cover all your ground. Frequently monitoring these various aspects ensures that the model is performing as intended and helps the institution understand model limitations and reliance on assumptions.

3. Review of Model Framework and Environment

The model owner and model risk management team should periodically review products, exposures, activities, clients, and market conditions to determine if the model needs to go into redevelopment. It may be that the model will need updating or readjustment according to the current environment, such as in the case of the COVID-19 pandemic.

4. Limitation and Framework Monitoring

Evaluate your current model usage to ensure consistency with any limitations identified during the development and validation stages.

During both the development and validation of your model, limits on what the model can be used for and the conditions under which it should operate best should have been identified. Once up and running, it’s good practice to regularly re-examine whether the model is still being used for its intended purpose and that the scope hasn’t changed.

For example, a model designed for a 9-quarter forecast should not be used for longer-range planning. Similarly, a model limited for use in positive interest-rate environments will require methodology adjustments if it now needs to forecast in a negative rate environment.

To Wrap Up

As reliance on models continues to grow, management needs the support to “buy-in” to the model results. This gives them the confidence to know they can make strategic decisions for the institution based on model results. The market is constantly changing; so without a proactive ongoing model monitoring program, you run the risk that the environment your model was developed in will not reflect the reality today.

Having a proactive Ongoing Model Monitoring program will help keep your model up-to-date with the current climate and ensure you are supplied with useful projections and outputs for analysis. However, in order to benefit from this, you’ll need a plan, such as timelines for reviews and re-examinations of the model, ensuring consistency and validity across the board. Ideally, this program will be governed by policy and a management team to ensure these checks are run on an annual basis, at the bare minimum.

If you understand why ongoing model monitoring is necessary to keep up with the subtleties of the ever-changing market, feel free to get in touch with us. You can contact our team today or send us an email at to discuss areas your model management may currently be lacking. We would be happy to support your implementation of a proactive ongoing model monitoring program.

Written by Chris Mills, Senior Director

Christine MillsAbout the Author
Chris has over 25 years experience in financial institution modeling and has been leading MVRA’s model validation services and core deposit / loan analyses teams supporting strategic balance sheet and risk management for over 8 years. She brings a wide range of expertise across treasury, asset/liability management and model risk assessment processes. Experienced with multiple ALM models, she also is skilled in capital modeling, capital markets, liquidity and contingency funding planning, funds transfer pricing, model risk governance practices, and investment banking.


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