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“I think the risk management function at banks might be subject to more transformation the next decade than it was the last ten years. Not only is the financial world changing rapidly, also the risk functions have to cope with newer risks. Personally, I think model risks is likely an important one. Banks are already largely depending on models, but as we see increased data availability, advances in new modeling techniques and new applied algorithms, I foresee an increasingly expanding model use. Risk managers should therefore better understand and manage model risk (which is the potential for adverse consequences from decisions based on incorrect or misused model outputs and reports). This requires new tools and new skills. Although that is exciting and challenging in itself, there is also a tendency of the functions departments of banks to deliver at lower costs. So we have to solve the puzzle to achieve more, and in a more efficient way”.

Could you please explain how to master the production of an efficient model risk framework?

An efficient model risk framework starts with an enterprise model inventory. The bank should have full awareness on all models used within the bank through a central repository. It is important to realize that a model inventory is not just a list of models. For an inventory system to create  value it should be a “smart data base”. It’s primarily use should be to get an aggregated view on the model risk of the bank and pinpoint areas of concern and opportunity. Likely those models that incorporate estimates of future client or market behaviour will pop up as most concerning. Also too complex models which are not completely understood at board level are risky ones.
An efficient model management of the complete model life cycle is also a great result of the model inventory. If the inventory is accurate and complete, it can streamline and manage the complete model review/validation/approval process. I think we should end up in better analytics or better models, optimize the model landscapes (maybe less models) but also become far more agile in the modeling process. As a result the model risk function may be able to make faster and better decisions at lower operating costs.

Which are the most effective methodologies to avoid the pitfalls of malfunctioning models?

In this effective challenge of model is key. Models are too complex and mistakes are too important to just develop them and next start using them. Basically not any model is right, but some of them are useful. You need an independent review or validation team to give you the message in which circumstances the model is adding value (and in which not). Even more important is that within the bank even at executive level understanding of models and model risk is key.

Why is it important to empower risk intelligence?

As stated before I think the risk function is going through change. It was already the function employing the “smart” guys and girls of the bank. But, they were unable to get always the message across. Partly because we made it too complex as well. So empowering risk intelligence is part simplifying the messages as well. Most banks are currently simplifying their businesses nowadays. But is not smart to put things simpler than they are. There comes the smartness of the risk manager back in the play.

What would you like to achieve by attending the 9th Annual Pricing Model Validation?

I think it is great to network in the current financial situation where so much recognition is given to modeling and validation tasks. Most important I’m really looking forward to meeting so many bright and talented people working in the industry. This pricing model validation conference gives an outstanding opportunity to learn from  others in the field.