Why all actuaries should be pro coders

As an actuary working at a technology company, I get asked a lot about the role of coding in the modern actuarial toolkit. There’s still plenty of debate around low-code, no-code, and pro-code approaches. Which is best? Who should be coding? What if your team isn’t technical? And where does AI fit into all of this?

The short answer is: it depends. All three approaches have their strengths, and each one can be the right fit in the right context. But as AI becomes more engrained in pricing teams, and as insurers push to modernise faster than ever before, I believe actuaries need to understand where these tools shine, and where they fall short.

In this piece, I’ll break down what we mean by low-code, no-code, and pro-code, explore what each unlocks, and explain why coding (especially in a pro-code environment) is one of the most powerful tools actuaries can have in 2026 and beyond.

What do we mean by Low-Code, No-Code, and Pro-Code?

Let’s start with some quick definitions:

It’s also important to draw a distinction between coding, and a pro-code solution. There’s a big difference between spinning up Python or R on your local machine to build something from scratch, and working within a pro-code platform that’s designed to support enterprise-grade actuarial work and analysis. The former gives you full creative freedom, but also comes with all the burdens of implementation: version control, access management, deployment, security, deployment infrastructure and maintenance. That’s where true pro-code solutions come in.

Platforms like hx aim to give actuaries the flexibility and creativity of open-source coding, while abstracting away the heavy lifting. You get the freedom to build, experiment, and deploy robust pricing models, without needing to hire a team of software engineers to support you. It’s about empowering actuaries to do more of the most high-impact work without getting bogged down in the plumbing.

Pro-code, low-code, and no-code all have their benefits and their trade-offs. Understanding them helps us decide when and where to apply each.

What can Low-Code and No-Code unlock for insurers?

For pricing actuaries, these platforms can offer some key advantages, but typically only in relatively simple, fixed or narrow problem scenarios. Low/no-code tools can be very effective in quickly solving specific pain points, but the second that scenario evolves beyond its initial specifications, tools quickly struggle to keep up.

If you’re looking for a solution to a more simple pricing challenge, perhaps in personal lines for example, then these tools could be the right choice for you. But be wary that unlocking longer-term value and the ability to deal with more complex or sophisticated problems will always take a hit.

In many ways, no/low-code solutions are the spiritual successors to Excel. Just as Excel and other early frontier Actuarial software made modelling, analysis and tool development accessible to a generation of actuaries, low-code tools are now helping teams automate repetitive tasks, and move faster. For many teams, especially those in more straight forward lines of business like Life insurance, low-code solutions can prove to be the right choice.

However, like Excel, they come with limitations. As models grow in complexity and data volumes increase, or as the desired analysis/use starts to deviate slightly from the simple/expected path, these tools can start to creak under the weight. Low-code platforms are often one-trick-ponies, and to solve increasingly complex problem scenarios, you can find yourself having to purchase a suite of different low-code point solutions. This then presents a new challenge of attempting to integrate all of these different tools into a single unified workflow, which can quickly spiral into an unexpected technical infrastructure resource drain. Exactly the type of challenge you were hoping to avoid by choosing a no/low-code platform to begin with!

Where do pro-code platforms deliver value?

From my own 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, problems and scenarios. The real power, especially when working with large, intricate datasets, or truly complex problems, comes from pro-code solutions that enable actuaries to build scalable, high-performance models tailored to their exact needs.

Some of the key benefits include:

This isn’t just about building more complex models. With pro-code, you can enable entirely new approaches to risk selection, pricing segmentation, and performance monitoring that simply aren’t feasible with more rigid toolsets.

How AI is impacting the coding debate

AI certainly is a critical piece of the puzzle as it's already proven its ability to enable high quality professional coding with a much lower technical barrier to entry. The ability to engage with agentic co-pilots, or virtual actuarial assistants, and interface with a complex pro code environment via text prompts in your native language is genuinely game-changing.

AI can drastically reduce the historically steep learning curve for coding languages - democratising access to pro code environments and widening the pool of people who can meaningfully engage with them. ChatGPT can already explain syntax, find and fix bugs, or quickly translate between coding languages. But, for now at least, there's still a critical need for an expert human in the loop who can properly interrogate the output, and actuaries with underlying coding knowledge will likely find it far easier to extract maximum value from the AI tools they engage with.

On top of the above, actuaries with coding knowledge can leverage AI in other ways. One key example is in experimenting with automation via AI API end-points - why not build a tool to hook into OpenAI's ChatGPT API and automatically pull in additional insight for that analysis you're working on? The possibilities for AI implementation in pricing workflows, and in complex risk management more widely, are vast, and the pace of innovation is mind-blowing.

As an actuary, why should I learn to code?

If insurers do chose a pro-code solution, there’s another important step. You need to get actuaries on board.

With very few exceptions - I believe every pricing actuary, especially juniors, should be learning how to code. That’s true even if the organisation they work for is firmly low- or no-code, with no plans of changing that. Here’s why.

You already have the mindset. Actuaries are technical by nature. Almost every actuary I’ve met is drawn to logic, patterns, and problem-solving. Coding is just the logical next step, and we've already seen the inclusion of coding in actuarial exams - so there's no turning back at this point! Importantly, because you have the full business context, when actuaries code, magic happens: fewer mistranslations, tighter feedback loops, and better products. You’ll also find yourself in a much better position to de-bug and self-serve when new problems arise.

Coding has never been easier to pick up. Python, R, and SQL are intuitive, well-documented, and supported by thriving communities (not to mention AI assistants that can practically write it for you). If you can pass actuarial exams, you can absolutely learn to code to a good standard.

Finally, it’s a versatile skill and a career accelerator. Actuaries who can code are in high demand. Want to work on cutting-edge pricing platforms? Be the go-to person for model deployment? Get noticed for taking your team to the next level of insight and automation? Coding is your ticket to bigger projects, faster promotions, and more influence in the room.

One of the challenges with some low- and no-code tools is that you're often learning to use a very specific solution to solve a very specific problem, something highly tailored and narrow in scope. That’s fine until you need to do something new, move to a different team, or change companies, at which point, those skills may not transfer.

Coding, on the other hand, is a foundational skill that applies across tools, teams, and even industries. It gives you flexibility and longevity.

The shift is happening. I see more actuaries picking up coding every year. But not everyone is moving at the same pace. There are still senior leaders who aren’t familiar with or supportive of code, and that creates friction. For years, non-technical decision-makers could rely on Excel as a shared language, just by opening up a spreadsheet and following the logic. With code, that comfort disappears. Unless leaders evolve too, they risk losing touch with how their team are working today.