The uncomfortable truth for insurance pricing leaders in 2026
If you lead an insurance pricing team in the UK right now, your world probably looks something like this:
Consumer Duty and regulation raising the bar on fairness and transparency
Claims inflation, weather and macro volatility battering your loss costs
Constant pressure to “use AI” and accelerate test-and-learn cycles
A hiring market where good pricing people are already in jobs – and everyone wants the same ones
And yet, the way most insurers hire and grow pricing talent hasn’t really changed in a decade.
Most are still trying to solve a structural capability gap with tactical backfilling:
“We’ve lost a senior analyst. Let’s go to market for another 3–5 years’ experienced pricing analyst who knows Radar and Python. Ideally from a competitor.”
Meanwhile:
Around 72% of insurers say they’re struggling to find candidates with the right tech and data skills, and nearly 60% worry they’ll lose staff to other industries.
Internally, many pricing teams estimate three to four months to fill core pricing roles, with attrition in pricing and data teams often above 30% over two years.
That’s not a strategy. That’s an auction.
At FlarePeople, we don’t think the issue is just supply. It’s how pricing teams design their talent systems.
Why the old hiring model is now actively working against you
Most pricing hiring strategies are built on three assumptions:
Experience is the safest proxy for impact
The market will always supply more mid-level talent… eventually
Pricing capability = number of heads + years of experience
In 2026, all three are wrong.
1. Experience is no longer the best predictor of value
What you actually need now are:
People who can learn new tools quickly, not just those who’ve used last decade’s stack
Analysts who can interpret models in a Consumer Duty context, explain decisions to the Board and work cross-functionally with product, claims and risk
Team members who can ship experiments, not just build models
But most job descriptions are still written as if:
The main differentiator is which version of Radar someone has used
Past employer brand matters more than learning velocity
So you end up in a global auction for a shrinking pool of “finished article” pricing people… while ignoring people who could get there with 10 weeks of focused training.
2. The future supply of pricing talent is not guaranteed
The pipeline behind you is thinner than it looks:
Only 4% of young people in the UK say a career in insurance is appealing. (covermagazine.co.uk)
Around 25% of the insurance workforce is expected to retire within 10 years, and in the London Market roughly half of employees are already over 40. (insurancetimes.co.uk)
If you’re banking on “we’ll just poach from competitors when we need to”, you’re betting your pricing P&L on a talent pool that is ageing, unattractive to younger talent and being raided by tech, fintech and consulting.
3. Headcount ≠ capability
Look at your team honestly:
How much of your pricing roadmap is stuck because one or two people are the only ones who can productionise models or interpret results?
How many initiatives slip a quarter because a critical role sits empty for 90–120 days?
How often do you compromise on hire quality because the business “can’t wait any longer”?
You don’t just need more people. You need:
Backup capability in key skills, so if one person is unavailable, another can immediately step in and own the process
Repeatable onboarding and training, so new joiners hit useful productivity in weeks, not months
Diversity of backgrounds and perspectives, because pricing is now as much about customer outcomes and behavioural insight as it is about GLMs
That is a design brief, not a recruitment brief.
Reframing the problem: from “filling roles” to “designing a pricing talent engine”
Here’s the mindset shift the highest-performing pricing leaders are making:
“My job isn’t to fill vacancies. My job is to design a system that converts raw potential into pricing capability at scale.”
That system has four components.
1. Hire for learning rate, not just tool experience
Instead of asking, “Has this person used our pricing stack?”, start asking:
How quickly can they learn a new tool or language?
Can they reason through an ambiguous pricing problem from first principles?
Can they communicate with non-technical stakeholders, defend trade-offs, and connect models to customer outcomes?
In practical terms:
Replace some “3–5 years’ pricing experience required” lines with clear capability outcomes (can build and explain a GLM; can design and run live tests; can work in sprints with product).
Use aptitude and problem-solving exercises in your hiring rather than relying on CV filters.
This is where non-traditional pathways shine:
Strong STEM grads
Ex-forces professionals used to complex, structured analysis
Career returners with serious stakeholder experience
All can reach pricing-ready capability with the right training route.
2. Build structured “pricing academies” instead of ad-hoc onboarding
You’ve fought hard to find and hire a new pricing analyst – and then most insurers do this:
Week 1: laptop, logins, mandatory e-learning
Weeks 2–8: “shadow Sarah and pick things up as you go…”
That’s not good enough when the tooling, regulation and competitive landscape are moving this fast.
A better design:
A defined curriculum for all new pricing analysts – tools (GLMs, Python/R, Radar), data foundations, insurance context, and Consumer Duty implications
A mix of classroom, case studies and live projects, so they practice with your real data and constraints
A 10-week pathway from “raw potential” to “can own part of a pricing workstream” – whether you run it internally or partner with a specialist recruit-train-deploy provider
The point isn’t to recreate a generic graduate scheme. It’s to compress time-to-value and make your capability growth predictable.
3. Expand where you look, but narrow what you’re looking for
The general insurance sector has a well-documented perception problem with younger talent and traditional pipelines under-serve women, career-changers and ex-services professionals.
So change the inputs:
Treat grads and early-career analysts as a long-term pricing asset, not cheap labour
Create a structured route for career returners (for example, those who’ve been out for caring responsibilities) – they bring resilience, maturity and stakeholder skills your team probably lacks
Look seriously at ex-armed forces talent for operations and analytics roles – they’re used to complex systems, disciplined execution and continuous learning
But be ruthless about the output:
Everyone, regardless of route, goes through the same pricing academy
Everyone is assessed on the same capability framework – technical skills, commercial thinking, communication and behaviours
You’re not lowering the bar; you’re widening the gate and then training people up to a clearly defined standard.
4. Measure what actually matters
Pricing leaders obsess over model performance metrics – but often have little visibility over talent metrics beyond “time to hire” and “attrition”.
If you redesign your talent system, start tracking:
Time-to-productivity – how long before a new hire is running their own analysis or owning a model change?
Capability coverage – for every critical skill (e.g. Radar deployment, Python automation, risk pricing), how many people can do it confidently?
Internal progression rate – what proportion of your senior analysts and leads have come through your own pathways vs lateral hires?
Diversity at senior levels – for example, % of senior roles held by women and ethnic minority colleagues
Once you measure these, conversations with the Board change from:
“We’re short three heads”
to:
“Here’s how we’re de-risking pricing delivery over the next three years.”
So, what should you actually do this quarter?
If you want this to be more than a nice read, here’s a concrete 90-day plan:
1. Red-pen your next pricing job description
Strip out “years in role” and employer brand requirements
Define the 4–5 capabilities the person must demonstrate in the first six months
2. Pilot one non-traditional pathway
Ring-fence 1–2 roles for high-potential candidates from outside traditional pricing backgrounds – grads, ex-forces, or career returners
Run them through a structured pricing training route before they hit the team
3. Put a pricing academy at the centre of your hiring
You need a defined learning path for all new analysts: tools, data, insurance context and soft skills
Reuse it for every hire – or plug into a ready-made pricing academy (like FlarePeople’s) if you don’t have the bandwidth to build and manage your own
4. Set one new talent KPI for your team
For example: “Reduce time-to-productivity for new analysts by 30% over 12 months”
Or: “Double the number of people who can independently own a pricing test.”
5. Ask one uncomfortable question in your next ExCo or Board pack
Not - “Can I hire three more heads?” but: “Are we prepared to invest in a insurance pricing talent engine – or are we comfortable with our current level of delivery risk?”
The next pricing advantage won’t come from a model – it’ll come from how you grow talent
Your models, data and regulatory environment have all evolved dramatically in the last five years, but if your approach to hiring and growing pricing talent still looks broadly the same, that’s your biggest pricing risk.
The organisations that win in the next cycle won’t be the ones who pay the most for the same small pool of mid-level analysts. They’ll be the ones who design and run a repeatable system that turns overlooked potential into real pricing capability, year after year.
And that’s a challenge squarely on the desk of pricing leaders – not just HR.
Let’s talk
At FlarePeople, we design and run the Pathfinders™ Academy specifically for insurance pricing teams. If any of the points above ring true, now is the moment to do something different with how you build pricing capability.
Visit FlarePeople to explore what a pricing talent engine could look like in your organisation or contact us: