The UK’s insurance sector is running some of the most complex and expensive technology programmes in British financial services.
Legacy core system replacements on platforms like Guidewire and Duck Creek that take two to four years to deliver. Cloud migrations of policy administration estates that have been running on mainframe since the 1990s. Data platform builds that are meant to become the foundation for AI-driven underwriting and claims. And, in the Lloyd’s market, a market-wide digital modernisation effort whose original vision has now been formally retired after five years of delays, leaving individual firms to execute their own technology strategies independently rather than waiting for a collective solution.
These are not small bets. A KPMG study (published in 2025) found that thirty-five percent of insurance leaders believe updating legacy technology architecture will deliver the greatest profitability gains over the next two years. The investment reflects genuine conviction. The delivery record is considerably more mixed.
What goes wrong is rarely the strategy. It is the execution layer. Let’s explore.
Where transformation programmes actually fail
The most common failure mode in large insurance technology programmes is not technical. It is human.
Programmes stall when the team doing the work does not have deep enough knowledge of the insurance domain to make good decisions at pace. A platform engineer implementing a Guidewire PolicyCenter configuration who does not understand how a UK motor insurer’s policy lifecycle actually works will make configuration choices that seem technically correct but create operational problems downstream. A data engineer building pipelines for a claims analytics platform who has never worked in insurance will not know that certain claims fields have specific regulatory constraints on how they can be used in pricing models.
These are not catastrophic failures. They are the kind of quiet, accumulated decisions that extend timelines, increase rework, and erode programme confidence. By the time they surface in a programme review, the project is months behind schedule and the conversation has shifted from delivery to recovery.
The talent shortage makes this worse. More than fifty percent of insurers now cite talent as the top obstacle to digital transformation success. The people who understand both the technology and the insurance domain are a genuinely scarce resource. The response has generally been to bring in senior consultancy resource to fill the gap. That solves the delivery problem in the short term. It does not solve the capability problem, and it is very expensive while it lasts.
The domain knowledge problem is not going away
One of the less-discussed risks in insurance transformation is the knowledge concentration that exists in legacy systems. In many carriers, the people who understand why the legacy systems are built the way they are, the business rules embedded in decades of policy wordings, the claims handling logic that evolved through regulatory changes, the pricing assumptions baked into actuarial models, are approaching retirement. According to the Chartered Insurance Institute, a quarter of the UK insurance sector’s workforce will retire within the next decade.
When those people leave, the institutional knowledge leaves with them. Transformation programmes that are still running when that happens face a specific and underappreciated risk: the team that was supposed to guide the new system through testing and validation no longer understands the old one well enough to know when something is wrong.
Replacing that knowledge with junior talent that was trained generically, without domain grounding, does not solve the problem. It extends it into the new system.
What lower execution risk actually looks like
The firms doing this well are building domain knowledge into their delivery teams from the start, not hoping it will develop over time.
That means recruiting early-careers technical talent with the explicit intention of training it to the client’s specific insurance environment before deployment. Not generic data bootcamp graduates. Not software engineers who have never seen a Lloyd’s slip or a Guidewire ClaimCenter configuration. People who arrive on programme knowing the tools, the data structures, and the business context they are working in.
An inclusive Approach to Solving Talent Gaps
Our Recruit, Train, Deploy service is structured around exactly this. We build a training curriculum for each client that reflects the specific technology environment and programme context the associate is joining.
For a carrier replacing a legacy policy administration system with a modern cloud platform, that means associates trained in the relevant platform, the policy lifecycle structures, and the data migration considerations specific to that class of business.
For a Lloyd’s syndicate building an AI underwriting capability, it means associates who understand the market data standards, the risk classes being underwritten, and the modelling environment they will be contributing to.
Associates are then deployed on a two-year contract with no employment liability and no FTE commitment. The pilot entry point, typically five to ten associates aligned to a specific programme, is designed to be low-risk and fast to mobilise. Clients have a full view of the associate before deployment through a client-led assessment process. At the end of the two years, conversion to permanent employment is fee-free.
"Every large transformation programme I have seen struggle in insurance has struggled for the same reason. The strategy was fine. The technology choices were reasonable. The team doing the work did not have deep enough knowledge of the environment they were building in. The way to reduce that risk is to solve it before deployment, not after go-live.”
Rick Hughes
Director, Corecom Tech Academy
Final Thoughts
The insurance sector is spending heavily on transformation.
The programmes are real, the technology choices are increasingly sophisticated, and the business case for delivery is clear.
What determines whether that investment produces lasting capability or expensive rework is the quality and domain depth of the operational layer doing the work. That is the variable that is most often underinvested in, and the one that matters most.
Looking to accelerate delivery across insurance teams?
Contact our team today to discuss how we can strengthen your capability and reduce risk.
