‘I preferred maths and physics, but when I wasn’t selected in the lottery, I opted for econometrics. I took a minor in Risk Management for Financial Institutions alongside that. At the VU, I spent a further two years teaching students on this minor. After completing my degree, I took up an internship at Nationale-Nederlanden. The financial world turned out to be the ideal environment in which to apply what I’d learnt. I was able to move to Zanders, where I’m currently involved in consultancy work on risk management for financial institutions. It’s true, I’m still young and, in theory, could change jobs many more times, but I’m happy where I am at the moment.

In my view, the introduction and promotion of the ESG framework has been one of the most significant developments in the financial sector. For a very long time, our sector turned a blind eye to this. The 2015 Paris Climate Agreement marked a turning point. All manner of regulations followed and portfolios were overhauled. Unfortunately, following Trump’s election, we are already seeing the consensus on ESG in Europe – which until recently enjoyed broad support – begin to crumble once again. The ECB remains firmly committed to ESG, but the European Commission is moving away from it, with an eye on trade and competition with the US. Will ESG regain its standing once Trump disappears from the political scene? Or will it have been completely sidelined by then?

If we’re talking specifically about the Netherlands, the pension transition is a major development. The old system worked well enough, but was impenetrable to most people, even though financial literacy in the Netherlands is relatively high. I expect the new system, with the introduction of the personal pension pot, to be much more transparent. You’ll soon be able to see exactly what’s in your pot at any given time. That’s a step forward, I’d say.

AI is set to radically transform the financial sector. We naturally already use AI in our consultancy work, but in our business cases we hardly take the benefits it brings into account yet. Sooner or later that will happen, because AI already enables us to do much more in less time. It remains to be seen, however, how the costs of AI will be managed. We can still use it ‘cheaply’ at the moment, but behind the scenes, staff and data centres have to be paid to train the models. Computing power and accurate data are absolutely crucial. The financial picture is still unclear, but it seems unlikely to me that it will stay that way. If users eventually have to pay for AI, will the business models of companies using AI remain profitable? Or will they temporarily do without AI again? And what are the societal costs of AI? Data centres are continuing to expand and consume enormous amounts of energy. Meanwhile, our electricity grid is already overloaded. What does the continued development of AI mean for our sustainability goals? Shouldn’t we start to manage the growth of AI? Will there even be anything left to manage? In short, we have a great many interesting calculations to make and questions to answer in the near future. It is also likely that a significant amount of new regulation will be needed.
 

You mustn’t underestimate the risks. But not every risk is equally likely to materialise.

 
How we can and must anticipate our future approach to AI is, naturally, a central theme in my work. Risk management is, of course, another key theme, as it is our core business. It is our responsibility to ensure that our clients’ data is of the very highest quality, and we are increasingly helping them with this, so that they (or we) are able to create appropriate models. A related factor is the complexity of the systems we encounter at major financial institutions. Acquisitions make these even more complex. Data systems change, and the requirements for them change. The layering of systems can increase the likelihood of errors.

Mind you, financial institutions in the Netherlands are generally doing very well. Banks and insurers go to great lengths to ensure their systems, administration and data are in order and to demonstrate this to their customers. Just look at the speed with which an organisation such as Independer is able to reliably collate and analyse online data from different but comparable sources side by side, examining aspects such as costs and product details. A price is generated instantly, even though the risks underlying the calculation models are complex. That’s truly impressive! Our company’s objective is to use our expertise and experience to identify risks at financial institutions, advise on appropriate control measures and help these institutions minimise errors as much as possible. Our understanding of the subject is broad enough to do this. The layering of systems within institutions – which we were just discussing – and the resulting complexity do, however, entail additional risks. For example, this layering can cause delays in the progress of processes, meaning that the figures used in calculations are not in real time but lag slightly behind. Based on my knowledge and experience, I understand the need for effective supervision of financial institutions. I also understand why data quality regulations have become increasingly detailed and why institutions are required to provide ever more precise data reports. One must not underestimate the risks. On the other hand, not every risk is equally likely to materialise.
 

If I can genuinely make a difference to a company and my actions have an impact, then I enjoy my work.

 
I regard the period during which I worked as an intern at Nationale-Nederlanden in a somewhat more flexible role as the most formative period of my career so far. I started there as an analyst and was able to take my time to explore which financial topics and areas suited me best and where I would like to focus my energy. I was given the opportunity to contribute to a complex project and provide the quantitative input for it: an investment proposal from Nationale-Nederlanden concerning the structure of their portfolio, which comprised a large number of different asset classes. This greatly expanded my understanding of and insight into all sorts of investment opportunities, and thereby also my own prospects for the future.

My most significant learning experience took place during one of my model validation projects. The validation itself wasn’t actually that complex. But the process that followed certainly was. The model owner and we didn’t see eye to eye. We identified shortcomings in the model, but our proposals to resolve them – the measures required and the associated additional costs and risks that we highlighted – were not endorsed by the model owner. Suddenly, I found myself playing a completely different game, and the discussion was about much more than just a quantitative debate on how a model works and the data that should be used. The discussions centred on questions such as what the impact of adjustments would be for the shareholders and for the management of the financial institution, and what would still be acceptable to the regulator. Given our independent role, we naturally insisted on clearly putting forward our opinions and findings. It wasn’t exactly easy, but it did make the process very interesting and instructive.

I certainly feel that I can apply what I learnt during my studies to my work and that I’m usually working on really interesting things here. Sometimes I feel that my work has too little impact. Model validation is absolutely vital, but if the economic situation doesn’t change much and neither do the variables within the model, well, then I just write my report and that’s that. If the model challenges me to make adjustments that improve a process, reduce costs for the client or enable the client to achieve better results, then it’s a completely different matter. If I can genuinely add value for a company and my actions make a difference, then I enjoy my work. Incidentally, it’s exactly the same with the voluntary work I do: when I see that my work makes a difference, I enjoy doing it much more. Whether it’s work for the chess world, looking after my grandmother, or taking part in the four-day wheelchair walk. How hard can it really be? For me, at any rate, it’s a minor effort; for the people I’m doing it for, it really makes a difference.
 

We’ve still got plenty of interesting calculations to make and questions to answer in the near future.

 
If you ask me about diversity and inclusion, I think these are important issues when it comes to the way we work together here as colleagues. Everyone is equal and everyone’s opinion deserves to be heard. But I’m not in a managerial role here where I help determine recruitment policy. For the time being, my influence is limited to asking questions and highlighting the importance of diversity and inclusion where relevant. In the world of chess, where I am active in an administrative capacity, I do have the opportunity to actively promote diversity and inclusion. I consciously try to encourage more girls and women to take part in training programmes specifically designed for them and to participate more often in tournaments and other events. There is absolutely no reason why the sport of chess should want to retain its image as a male-dominated sport.

Making an impact is a driving force for me, but so are enjoying time with colleagues and finding joy in my work. People do say that you work to live, not live to work. For me, I work with pleasure so that I can have even more fun. If I were to lose that enjoyment, it would be time to look for a new job. Of course, I enjoy more things than just my work or a game of chess. I love going for a bike ride – it’s brilliant! And I enjoy playing games. Not computer games, but board games like Catan or Carcassonne. With my family. Or the music game ‘Hitster’ – that’s a big hit with us too. When I moved out on my own, the first thing I bought was a whole set of board games, because I missed them so much from home.’