(Originally posted on LinkedIn – July 2018 – updated with minor edits)
Since I began my second career as an actuary, my focus had been to excel as a traditional life actuary. But the recent rapid digitalization of our life, in general, set me thinking about what I would do if I had to start my career all over now? Insurance is drastically transforming, driven by data explosion enabled by the exponential increase in computing power. Cornea cancer can be detected better by AI than a trained medical professional; why not do risk quantification better by AI? Where do we see our professional career heading? To stay relevant, or rather, be at the forefront of disruptive changes upsetting traditional business models, we need to be proactive.
With my actuarial professional experience and active interest in InsurTech, I would have loved to be more broad-based in the following areas. Of course, depending on geekiness or otherwise, one could focus differently based on personal preferences. Still, we actuaries will need a decent mix of all these areas to excel in changing insurance domain.
Core Actuarial skill sets
Unlike other financial specialists, actuarial training is unique, tuning us on a long-term risk horizon. As a result, we specialize in valuing reasonably long uncertainties.
The professional training gets us two skills that are crucial niche capabilities. One is being able to visualize risks into cash flows. We learn to blend the frequency and impact of events, management expenses, capital requirements, long-term regulatory implications, and overall macroeconomic outlooks. The other is our bread and butter, being able to transform this visualization onto spreadsheets. Developing a reasonable back-of-the-envelope model and detailed cash-flow models is crucial for our professional excellence.
To hone these skills, I would have started with life events. Plain term insurance is the easiest to begin with, has a good blend of long-term complexities with established modeling practices. Developing a simple annual model helps to understand how to estimate the cost of insurance. Deal with mortality and expenses first. Gets you a basic sense of cost. Then introduce the lapses, interest, risk discount rate, reserves with best estimates, margins, taxes, and risk capital, one at a time. Follow through how these impact the cash-flows by watching components of present value costs as % of the premium, over different ages. It will be very revealing learning.
Once you are comfortable, explore models for term assurance with the return of premium, endowment, and whole-life benefits. I did this exercise with a batch of complete novice students from Christ University, Bangalore. I learned new perspectives despite having spent more than a decade creating, testing, and auditing these models myself!! Looks simple, but few learning plans for actuarial students focus on this.
This is a strong foundation for extending these concepts to any other risks. Try out with different insurable risks like health, critical illness, property and casualty, catastrophe insurance, etc. Any long-term financial projects can be analyzed this way.
Large data volumes
Being comfortable handling tons of data and some decent coding capabilities – No way hiding from these two. With the digitization of our life, data will come into our daily work with ever-growing volume and complexity. New technologies will be emerging to cope with this volume, enabled by equally fast-faced computing power growth. While data analysts can help us get more and more trends and patterns, we would have a sense of what and where to look for as risk experts! Knowing a fair bit of coding will go a long way in working with data experts; speaking their language. What can be done, and what is possible, where to look with overall risk perspective.
Code also will help you to automate. I am currently enrolled in Python and Machine-Learning, feels exhilarating! Get to learn Python, learn R; the sooner you do, the better. They will expand your ability to adapt, improve, and help you to be skilled in visualizing risks and patterns from data.
This is my life bet. My associates laugh at my obsession with Blockchain, but I wish I was 20 years younger as I watch this space! Increasing computing power has made Blockchain possible. There are tons of whitepapers associated with ICOs explaining how they visualize breaking and recombining traditional business models, driving down the costs to unbelievable levels. Our current business models of facilitating insurance as a shared pool of risks will no longer be sustainable. With that, the scope of actuarial jobs will change as well.
Knowing how Blockchain works can make way for developing a very niche profile. Actuarial, legal, and financial experts need to start thinking about adapting our business to smart-contracts, event-based financial actions that can be coded explicitly. Those early starters will be really sought after five years from now. Visualizing the risk events and their consequences and turning that understanding into executable code will be a sought-after skill. Would pay a fat salary too, probably way more than traditional actuary skills would do in the future.
Start learning Solidity; I am currently on my way to developing my first smart contract. Trust me, it feels terrific! It’s not that tough, more like Java. The whole ecosystem is fascinatingly evolving and so rapidly transforming. Coding is really learning to think in logical steps. You understand any one language, and you have basic grammar in place. It’s just then adapting to specifics of operating environments or building on specific capabilities of the coding language.
Hope this helps and encourages some of our young budding actuaries to choose to become like, Blockchain Actuary!