I've studied econometrics, which is similar to actuarial science in many respects and worked in leadership and consulting roles in the financial industry with banks, insurance companies, and pension funds. For the last eleven years, I’ve worked for a Dutch insurance group that's operating in Europe and Japan. During that time I’ve worked with many actuaries.
Innovation is about people getting frustrated with how things are working and doing their best to think outside of the box to find new solutions for existing problems, or existing solutions from different fields that they can apply to those problems. Key characteristics are curiosity, keeping an open mind, being determined and passionate, being adaptive, and being flexible to change your own way of thinking.
The last part is maybe not so much a characteristic, but you need to be able to create dedicated time to put in the hard work to create those new solutions. In most insurance companies there's so much pressure, especially on actuaries, to work in pricing, to work in risk, to work in finance and there’s not always enough time to do some innovating.
I have this dream for actuaries where, ideally, the actuary who is a well trained lady or guy comes in, the data’s ready, the computer has done its job, and the actuaries do what they’re trained to do; make sense of complicated information and translate it into business decisions. In an ideal case the data is already complete, it’s clean, it’s accurate, and the analysis and visualization tools are working.
What factors influence that? The leadership needs to make sure what I just described is facilitated. There's also a role of the leadership to set clear priorities. If you have one actuary, you can only dedicate that person to a few topics. Also, it is about asking the right questions to these actuaries for them to perform their magic.
A long time ago I witnessed some of the discussions within the Dutch Actuarial Society around “What is the role of the actuary? What should we be doing? What are we created for?” That's a discussion that somehow keeps on coming back.
I don't see an actuary as that much different from myself, I studied econometrics, or from someone in a more mathematical or statistical background, a data scientist. An actuary is someone who can attack complex problems by looking at data, making sure we have the right data, apply certain techniques or models to that data, and then translate outcomes into something that makes sense for the rest of the world. An actuary has done that mostly for the insurance or the pension fields where we think about how to calculate the way people are going to live and what the risk around that is, or how we model behavior of people in the general insurance or life insurance field.
With all the advancements that we now see in data gathering, computation speed, calculation tools, visualization tools, AI, and ML, there are more opportunities for actuaries to use these in the insurance field to do even better analysis and provide better insights. I see the actuarial profession evolving alongside all the progress that we’re seeing in the data science field as a whole.
I can imagine that some actuaries will move more into the data science field to become actuarial data analysts. Whereas others will keep focusing on the vast knowledge they have of the insurance products and behavior to help the data analysts with problem formulation and making sense of that data.
We can also take a step back and realize that even with everything that is evolving, some things stay the same. In principle, all that I've been doing in my career, it's about step one, what's the problem? Step two, where's the data? Step three, how are we going to transform the data with models and calculation techniques? And step four, how do we present that to the outside world? That’s the mental map that I have for everything that I do.
If you have some affinity with numbers, math, and statistics, you like to solve puzzles, and at the same time you want to work in a field that is important in society, then go for it. I can’t really comment on the exact studies that you need to take, but having studied econometrics I thought it was a tough study. I had to roll up my sleeves and do hard work. The key thing that I took from that study, that I think will also hold true for actuarial studies, is that you build this analytical mindset to know how to slice and dice problems and optimize. Up to this day I've taken that with me in everything that I do.
As there's such an overlap between actuaries and data scientists, to me there’s not really a clash. Still, the leaders of the organization play a very important role here. A pure data scientist is different from a pure actuary but, given the overlap that we do see, it makes perfect sense for these people to work together. There will be actuaries who are very familiar and comfortable with all the data science tools and there will be data scientists who have a knack for insurance topics. Cooperation will become easier when you have that situation. If not, then as leadership you have to make sure that you have the right combination of qualities.
The most important thing is to keep an open mind and be appreciative of the qualities that the other party brings to the table that you can benefit from. Nobody can do everything, so you need that combination of skills. There's overlap and there’s complementary skills, we can make use of that.
You have to take a step back. What is innovation? Many years ago, there was a scientist from 3M who wanted to create a super adhesive material and he sort of “failed” which led to something not as adhesive as it should have been. They kept it on the shelf for years before they realized what you could do with it. It finally became post-its. That was a huge success, but for years they didn't even recognize it as innovation or having that kind of an impact.
In this case, they had a solution without a problem. An innovation is impactful if it provides a solution to a problem that is better, more efficient and cheaper, or more beautiful than current solutions. You have to think about some metric for how an innovation made things better. Sometimes you don’t realize the possible impacts for the innovation or you don’t recognize the innovation at all. That’s why I’m struggling with an answer to the question “what makes an innovation impactful?” It can actually take a long time before you see the impact of innovation.
I don’t think I’m the right person to comment on this, not being an actuary and not having studied actuarial science. From a broader perspective, actuaries work in some of the most heavily regulated industries in the world and it really limits the possibility for innovation. It is possible to innovate, but you can debate if that’s then an actuarial innovation or, for instance, insurtechs trying to disrupt the insurance field. In a lot of cases, you do see innovations coming from the outside in. Whereas from inside the field it's more incremental or in smaller steps.
With big data there will be more opportunities to try out new things and find new patterns. Most people nowadays have wearables that you can use to add to your existing data and historical data to improve the pricing, or get better estimates of the risks that you're trying to underwrite. There's huge potential.
On the downside, insurance is a difficult field to gather data in general. If you're a bank, every day something happens that creates data that you may be able to use. You have a bank account, now something is deposited, now something is withdrawn and you have certain behaviors that you can analyze. For insurance companies, there are less transactions so you have to think about what you can add to that data to make sense of it.
I started in the middle of the 90s when we moved to something as simple as email. You could see that as an innovation which made us more agile. I've seen in some parts of companies that innovation or change in general is welcomed and in other parts of companies that it’s not appreciated as much. I’ve learned in the actuarial and insurance field that we like our ways of doing things. When we have spent so many years studying for our skills and we have built tools in the past that work, why should we change? People think “I have this wonderful excel spreadsheet with all these links and formulas to other spreadsheets, please don’t ask me to change this because it is working and it is great!” It is sometimes difficult for them to find the time and make changes.
There are some things that you could describe as innovation, but not so much to the insurance field itself. It is, in general, more a result of the progress in computer power and data availability and storage. The use of data in underwriting with things like predictive underwriting, how you can improve your claims handling by automating it to a certain extent, fraud detection systems using data patterns, et cetera. I think those are innovations coming from the availability of more data than we’ve had in the past.
I always get a little bit suspicious with such a question because it presumes that actuaries are not influential enough. I'm not certain that actuaries need to become more influential. Actuaries are people I listen to carefully because these are people who are trained and experienced in products, customer behavior, financial risk and they really know how to connect the dots. I would say actuaries, because of their knowledge and experience, are already very influential. And rightfully so!
I would stress the key characteristics of an innovative actuary. I'm a big fan of actuaries, having worked with them for many years. I was often in awe of how fast they could see through problems and come up with solutions for complex puzzles. In the actuarial community, there's a bit of a fear to let go of the old and adopt something new. That's why I really want to stress having an open mind, curiosity, trying new things, being flexible and being adaptive. That's what we need to keep doing to stay as influential as actuaries are now.
I have this frustration that we have this immensely well trained and experienced group of people (actuaries) who are wasting their time making sure the cells are right in their spreadsheets and that the links are working. Then something is not working and they have to dive into it. We need a way to make sure actuaries can just come in, the data is cleaned, automated, the calculations are done and the dashboard has the outcomes. Now, do what you do best, and make sense of this complex information and make sure that we can create the best products, the best underwriting, the best claims experience, et cetera, for our customer. That will be awesome. I don't think we're there yet but we’re making steps.
