Building the foundations for a data-driven London market
As the London insurance market continues its digital evolution, one theme dominates every conversation — how to move beyond legacy technology without losing stability or focus. The industry’s ambition to become fully data-driven and AI-enabled depends on this critical step, yet for many organisations, modernisation remains a balancing act between maintaining core business continuity and preparing for the next generation of intelligent tools.
The case for modernisation
Legacy systems are more than a technical problem; they are a strategic risk. Outdated infrastructures constrain agility, make integration difficult and hinder compliance. Participants at the recent Beyond Legacy breakfast briefing emphasised that these systems often carry hidden operational vulnerabilities that limit resilience and innovation. Modernisation, therefore, is not only about improving efficiency but safeguarding the ability to adapt to new client demands, market practices and regulatory expectations.
The cost of inaction is mounting. As one participant put it, “Old tech doesn’t play nicely with modern tools”. Workarounds and end-user computing (EUC) tools may offer short-term relief but deepen technical debt and slow the pace of progress. To compete in a market that prizes speed, transparency and data-driven decision-making, insurers must address the foundations first.
The modernisation dilemma
Despite broad consensus on the need for change, firms continue to struggle with the practicalities. Demonstrating a clear ROI on system upgrades is difficult when the benefits are long-term or indirect. Funding and resource allocation are further complicated by the daily operational pressures that dominate attention.
Moreover, the complexity of interconnected legacy environments means incremental change is rarely straightforward. Many firms face declining internal expertise, limited documentation and risk-laden dependencies that make large-scale replacements daunting. “Complex landscapes restrict our ability to phase modernisation,” noted one contributor. The result is often inertia – not from a lack of ambition but from the sheer challenge of managing transformation without disruption.
Rethinking the approach
Modernisation is no longer a one-off programme; it is a continuous discipline. Reducing technical debt, integrating systems post-acquisition and embedding interoperability must become part of business-as-usual. This requires not just new technology but cultural change with a greater alignment between IT, data and operations, and leadership willing to champion both short-term wins and long-term architectural investment.
Interestingly, AI is emerging as both a disruptor and an enabler in this equation. Some leaders are beginning to question whether modernisation should focus solely on replacement or also on augmentation. Advanced AI models can now interface with legacy systems, automate manual processes and unlock data that was previously inaccessible. For certain use cases, AI may offer a more pragmatic bridge than a full rebuild.
A pragmatic path forward
There is no single blueprint for success, but clarity of purpose is essential. Modernisation must deliver stability, security and incremental efficiency today while enabling flexibility for tomorrow. It should be viewed not as a cost but as an investment in capability…the foundations upon which the London market’s data-driven future will rest.
The next phase of transformation will belong to firms that treat legacy not as a barrier but as an opportunity to re-architect intelligently, combining the resilience of existing systems with the agility of AI-enabled innovation.
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