By Jamie Wilson, VP of Growth at hyperexponential
I’ve always been curious about learning new things, and as my work started requiring me to pull data from databases, I found myself exploring SAS and SQL coding (and what I later discovered to be data engineering) almost out of necessity. What started as a practical solution to data challenges quickly became a passion. Over the years I dug into new languages (R and Python) and other applications beyond data 'munging' including statistical modelling, portfolio analysis and data visualisation. Now I’m an actuary working at a technology company, so it clearly came in handy.
But you don’t have to take the same path to see that the actuarial profession is changing. Technology is evolving faster than ever, and it’s reshaping our roles in ways that demand new skills and new ways of thinking. I believe actuaries who embrace technology—not just as an enabler, but as an integral part of their work—will be the ones shaping the future of our profession.
Technology at the heart of pricing
Historically, some actuaries have been wary of embracing technology beyond Excel. I’ve sometimes heard "the data team will fix that" or "that’s IT’s responsibility" or my personal favourite "but if it's not Excel, how will we be able to see what's actually happening?". Imagine, instead, an insurer with a powerhouse actuarial function at its heart—one where actuaries don't wait on IT or external data teams but are fully empowered to shape, manipulate, and control data and deploy insights/strategy to the wider business themselves.
I’ve long believed the real strength of the pricing function comes from embedding deep technical capabilities directly within the business itself. The same is true of data and analytics. By building these skills into actuarial teams, insurers can unlock extraordinary value. So, what are the next steps to truly becoming a technologically advanced function that can create outsized value?
We should all be coders
I’m going to come in strong out of the gate here and say that I believe every pricing actuary (especially those who are early in their career) should be learning how to code. Here’s why.
Actuaries are inherently technical professionals, adept at numerical analysis and logical problem-solving. Coding is simply a natural extension of our existing skills, while enhancing our ability to navigate increasingly complex data and risk environments and build the most sophisticated models. There’s an outsized benefit achieved when individuals with the business and technical knowledge deliver technology solutions. If you rely on data teams to do the coding, they don’t necessarily have the insurance knowledge or context to know what data to surface in which way, or what to prioritise. It’s the same with pricing tool implementations, or other technology deployments. Ultimately, actuaries coding can unlock faster, higher-quality solutions tailored to business needs.
Furthermore, coding is far more accessible today than it ever has been. Twenty years ago, languages like C++ posed a daunting learning curve, typically reserved for dedicated software developers. Today, the rise of user-friendly languages such as SQL, Python, and R has dramatically lowered this barrier. That’s not even touching on how AI Co-Pilots can accelerate your both coding and the learning curve, which we’ll dive into more later.
Coding can also be an incredible career accelerator. In the London insurance market, for example, I’ve seen first-hand how actuaries with Python skills are increasingly in demand. Insurers want talent that can ramp up quickly with modern pricing software, and coding proficiency is becoming a key differentiator. Within your organisation, coding can also expand your influence by making you more of a strategic player.
At the end of the day, Excel becomes a limiting factor in what Actuarial teams are able to achieve. I once built out a spreadsheet to manually run simulations on different frequency/severity distributions. If I were to do that today, I’d be writing the same code in Python. It would take seconds (don’t believe me? ask ChatGPT) and would also be significantly more flexible, performant and powerful.
I fully accept that Chief Actuaries who aren't involved in hands on, day to day work don't necessarily need to spend their weekends and evenings getting their Python skills to a market leading standard. I do however think at the very least there is a responsibility on leaders within the actuarial profession to embrace this change and promote coding as an opportunity for their teams as opposed to enforcing Excel be used for a specific process/piece of analysis because it always has been. But if you do happen to find yourself with a free evening, why not crack into some Python with that glass of wine?
Pro-code at the heart of pricing
This talk of actuaries and coding naturally leads us to the discussion of whether code needs to sit at the heart of your pricing; weighing up low-code, no-code, and pro-code solutions. Low no-code tools certainly have their place. They’re great for getting teams up and running quickly, particularly for simple datasets and actuaries who are just beginning to build technical skills. However, these solutions often hit a ceiling as complexity grows in the same way as Excel does. In my experience, low-code tools provide a helpful starting point but rarely support the depth of analysis or flexibility needed for the most complex pricing models. The real power, especially when working with intricate dataset, or complex problems comes from pro-code solutions that enable actuaries to build high-performance models tailored to their exact needs. Ultimately, maintaining curiosity about technology and constantly evaluating where coding could be unlocking stronger outcomes is key.
The AI enhanced actuary
Today, as actuaries we find ourselves at another exciting frontier: artificial intelligence (AI).
When I first started coding, I’d have loved to have AI-powered assistants and coding co-pilots at my side. These tools make coding and debugging exponentially faster, while lowering the barriers to learning. And that’s just the start; AI will also transform how we ingest vast datasets, perform deep analysis, and unlock insights in seconds that would have previously taken weeks. But there’s a gap between the technology being developed and the skills actuaries need to harness it. According to our annual State of Pricing report, 91% of insurers are already investing in AI technologies or plan to do so within the next five years. Yet, despite this, 80% of actuaries say they’re worried they don’t have the right technical skills for the future, particularly in areas like machine learning. More than half believe this issue is either urgent or will become urgent within the next two years.
Unlock AI (for yourself)
My core thoughts on how AI will impact roles as an actuary are similar to my thoughts on coding. If you want to succeed, push the boundaries and get the most out of your effort and your career, I recommend getting hands-on with this technology as soon as possible, even if you're not working at an insurer with a sophisticated AI roadmap or capabilities. Experiment, upskill, and think about what use cases could unlock the most value for your organisation. If you don't know where to start, Set up a ChatGPT account and start asking it questions.
I’m delighted to see that coding is now part of the core actuarial exams. Perhaps in the near future, we’ll see AI prompting or similar technologies included in professional qualifications. It’s a fascinating thought that underscores just how much our profession and the wider world is evolving.
Working faster and smarter
Actuaries have always been problem-solvers, using data to make sense of uncertainty. The tools we use may be changing, but the core of what we do remains the same. My advice is simple; these new technologies are here, they’re transformative, and getting ahead of them will open up new opportunities for you and your organisation.
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