Most conversations about insurance modernisation start with the destination. New platforms, better analytics, cloud-native architecture. The vision is always compelling. The slide deck is always beautiful.

But the conversation that actually determines what happens? That’s the one about what it costs to move. And it’s usually a lot less beautiful.

Policy migration — the work of lifting books of business from one system to another — carries a transaction cost that’s rarely discussed with the honesty it deserves. In the UK market especially, where legacy estates run deep and regulatory complexity adds weight to every data field, that cost doesn’t just affect project budgets. It shapes strategic decisions in ways that often go unexamined. Which is how “modernisation” turns into million-pound archaeology.

The Problem in Plain Terms

At its core, policy migration means taking every active (and often historic) policy record, extracting it from one platform, cleansing it, transforming it, validating it, and loading it into another. Every endorsement, every claim linkage, every underwriting note. Every workaround someone built in 2007 because the original spec didn’t account for something and nobody’s touched since.

For a mid-size UK insurer carrying a few hundred thousand policies, that’s not a weekend job. It’s not even a quarter job.

Industry figures paint a sobering picture. Gartner research suggests that 83% of data migration projects either fail outright, exceed their budgets, or overrun their timescales. The Bloor Group puts average cost overruns at 30% and time overruns at 41%. These aren’t insurance-specific numbers, but they land hard in a sector where policy data is uniquely complex — decades of accumulated business logic, bespoke product configurations, and regulatory audit trails that can’t be approximated. Or, as we like to say, a few decades of “we’ll fix it later.”

For large insurers, a full platform transformation can exceed $5 million, with timelines stretching to 12–18 months. And that’s when things go relatively well. The UK has its own cautionary tales — programmes where investments north of £300 million were ultimately abandoned without achieving their goals. That’s not a budget overrun. That’s an expensive lesson in not knowing what you were sitting on.

What High Migration Costs Actually Do to Decision-Making

Here’s where it gets interesting, and where we think the industry needs a more honest conversation.

When migration costs are high — and critically, when they’re unpredictable — they don’t just slow down transformation. They distort it.

Carriers stick with platforms they’ve outgrown, not because the platforms still serve them well, but because the perceived cost of leaving is too daunting. Product innovation stalls because launching on a new system means migrating the old book first, and nobody wants to sign off on that business case. M&A activity gets complicated when acquirers factor in the true cost of integrating policy books — something that’s bitten more than a few deals in the London Market, where legacy estates from multiple generations of underwriting can sit on top of each other like geological strata. Impressive to look at. Terrifying to move.

The London Market itself is a case study in this dynamic. Lloyd’s Blueprint Two programme — designed to move the market from paper-driven, legacy processes to a digital backbone — has identified over £800 million in potential cost reductions. DXC’s recent migration of London Market infrastructure involved moving 70 billion rows of data and more than 200 business applications. These aren’t footnotes in a transformation plan. They’re the reason the plan exists — and the reason it’s so hard to execute.

Even McKinsey’s finding that insurers with modernised technology stacks report 41% lower IT costs per policy points to a frustrating irony: the destination is clearly better, but the journey there carries so much cost and risk that many never set off. They just keep maintaining what they’ve got and hoping the problem ages out. It won’t.

The Economy Drivers Behind Migration Cost

So what actually drives these costs? A few things converge, and they’re worth naming — because understanding them is the first step toward changing the equation.

Data complexity and quality. Insurance policy data isn’t clean tabular information. It’s layered, version-dependent, and often held in formats that made perfect sense to the system that created them but translate poorly to anything else. When Experian research shows that 64% of data migration projects go over budget, data quality is almost always the culprit hiding in plain sight.

Regulatory and compliance requirements. In the UK, FCA oversight means that migrated data must be demonstrably complete and accurate. You can’t take shortcuts with policyholder records when the regulator expects full traceability. This adds validation cycles, sign-off gates, and specialist resource — none of which come cheap or fast.

Platform and vendor lock-in. The major policy administration vendors — Guidewire, Sapiens, Duck Creek and others — operate in a market projected to reach $31.6 billion by 2032. Extracting data from one ecosystem to move it to another isn’t always a straightforward export. Proprietary data models and custom integrations mean that what should be a data problem becomes an engineering problem. Sometimes an emotional one too.

Undocumented business logic. The rules, the workarounds, the “ask Janet, she knows” knowledge that exists nowhere except in code paths and people’s heads. This is the one nobody puts in the business case and everybody discovers mid-programme.

Organisational readiness. Migrations aren’t just technical. They require business sign-off on data mapping decisions, product rationalisation, and the inevitable gap between what the old system held and what the new one can represent. That human cost is almost always underestimated.

What Comes Next

We’ll be exploring each of these economy drivers in depth in a follow-up post, because they deserve more than a paragraph. The companies navigating migration well aren’t necessarily spending less — they’re spending smarter, using discovery-first approaches that understand the legacy estate before committing to a migration path.

That’s core to what we’re building at Metamorphic. Legacy systems aren’t the enemy — they’re full of the business logic and decisions that made companies successful. The challenge isn’t to destroy and replace. It’s to understand what’s there and make it usable, so that when migration does happen, it’s informed, targeted, and far less likely to join the 83% that don’t go to plan.

If you’re staring down a migration decision, or stuck in one that’s proving harder than expected, we’d welcome the conversation. No hype, no hand-waving. Just honest talk about complex systems.