The Importance of Risk Management for the New Bank

By Ebbe Negenman, Chief Risk Officer and Member of The Executive Board, Aegon Bank and Knab

Ebbe Negenman, Chief Risk Officer and Member of The Executive Board, Aegon Bank and Knab

Nowadays, banking is all about the customer experience. Is your bank giving you the effortless onboarding process? Is the latest technology fully embraced and working on your iPhone? Is your watch an alternative for the banking card? If not, you should be aware that the new entrants in the banking world already offer all these features. Surely this adds to better banking at this moment for the customer. And this is noticed by the incumbent banks. Consequently, these old banks are massively partnering up with Fintechs, are implementing agility in their IT departments, and more often you spot a CEO of an old bank without tie but with sneakers. This movement is great, but there is more risk than ever in the system. The tech banking world is extremely complex and less than a few understand the complex algorithms and the IT systems that are in the heart of the New bank. Consequently good risk management is now evolving in the conditio sine qua non.

“All models are wrong, but some are useful” is a famous quote of the British statistician George E.P. Box (1919- 2013). The truth of his statement was evidence by the Great Financial crises of 2008. In normal circumstances combining mortgages of averages credit quality in tranches, one tranche with lower than average and another with prime credit quality, provides a useful investment opportunity and is mathematical correct. However, it turned out in the extreme event all mathematically proven un-correlated events were in the reel world behaving completely differently. The model was not even useful anymore, even stronger we discovered it had navigated us in the opposite direction. Basing your investment decision on the outcome of models only is therefore introducing a new risk. The bank should have good risk manager in place for addressing this type of model risk.

Reel world is following its own principles. This holds for risk models as well. Even the methods that are in use to determine the likelihoods of extreme events can be completely wrong. A simple VaR model is commonly used by most risk management departments of banks on measuring market risk to survive all normal market volatility. In most banks the models are calibrated to capture about 99.95 percent of market movements. However in the crises we encountered market movements that were far in the tail of the 0.05 percent as predicted by these models. As a result, some banks literally claimed that the reel event they faced was a six sigma. Which makes it as rare as the origin of the universe. The 6 sigma is however computed with the model and therefore implicitly the assumption is made that the risk model by itself is good. But that is not likely as well, these events do not happen in a 30 year period (the VaR models are in use since the early 90’s). Indeed George E.P. Box statement also holds for risk models. So now we need excellent risk managers in the New bank, that are also able to reflect on themselves.

The whole digitation of banks is adding complexity and risk to the industry

The reaction of the governments on the crises was to extend regulation. Although the intention of regulations are by nature good since regulation is created to prevent a bad outcome happening again. But we should be aware that regulation creates risk as well. A simple example is again the VaR confidence level of 99.95 percent. This percentage is in the European law, which gives it regulatory support and therefore a certain trust. Furthermore, as a bank you are forced to use this percentage and the model (if you like it or not). Consequently the VaR figure will become the number you steer your percentage in a myopic way and unavoidable at some point the bank will be discover that events that were not predicted by the model will happen again. The fact that the law holds for everyone (i.e. all banks use similar models and the same likelihood), means that the rare event is not foreseen by all of us giving us a receipt for the perfect storm. Again the bank needs good risk management to differentiate from the herd.

The whole digitation of banks is adding complexity and risk to the industry. Basically banks are more and lead based on outcomes of complex algorithms. E.g., artificial intelligent and cryptography, can only be understood by educated mathematicians. Typically these backgrounds are not present at board level. Here the CRO has an important role, not only by providing a quantitative background, but also by challenging if the additional complexity is really needed, and if so identifying and managing the new risk that do arise.

All together risk management has never been more needed within the bank. It is already out of the back-office controlling role and is now growing in a full executive level function that is involved in any decision made. The risk role will be challenging however, since new risk will arise and events will happen that we are currently not aware of. Even more challenges are ahead of us, because in the digital world we have to act fast on events. Events travel much faster than before due to more connectivity than ever. In any case Risk is definitely an exciting place to work in.

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