By Jamie Allsop, Financial Services and Insurance Managing Partner at HTEC
The insurance industry stands at a crossroads. With customer expectations soaring and technological capabilities advancing at breakneck speed, many insurers find themselves trapped in a cycle of maintaining decades-old systems that consume the majority of their technology budgets. Industry data reveals a sobering reality: insurers are spending up to 70% of their technology resources on simply keeping legacy platforms operational, leaving precious little room for innovation or competitive differentiation.
This technical challenge poses a threat to insurers’ ability to compete in an increasingly digital marketplace. The companies that successfully navigate this transformation will turn their technical debt into a digital dividend that funds future innovation and growth.
The 70% budget trap
The mathematics of inherited legacy systems creates a vicious cycle that grows more constraining each year. As systems age, they require increasing resources to maintain stability, security, and regulatory compliance. Meanwhile, the skills needed to support these platforms are becoming more scarce and expensive. What begins as prudent system management evolves into a resource drain that starves innovation initiatives of the funding they desperately need.
This budget allocation forces insurers into a false choice between operational stability and competitive advancement. Companies that choose stability risk becoming obsolete, while those that prioritise innovation may compromise operational integrity. Successful transformations recognise that this is not an either-or proposition but a strategic orchestration challenge.
Rethinking business paradigms
Legacy modernisation extends far beyond replacing old technology with new systems. It needs a fundamental rethink in how insurers operate, serve customers, and create value. The rise of AI has made this even more urgent, as AI-first strategies demand flexible, data-rich platforms that legacy systems just simply can’t support.
Consider the insurance claims process, where AI can automate the collection and collation of data from multiple sources, like police reports, medical documentation, and legal filings, presenting consolidated information to claims handlers for decision-making. AI can improve fraud detection by spotting syndicate patterns and speeding up customer resolutions. However, these capabilities require modern data architectures and API-enabled systems that can integrate seamlessly with AI tools.
Consumer duty requirements, which demand evidence of good customer outcomes, fair value assessments across product lines, and personalised service delivery, rely on advanced data analytics capabilities that legacy systems struggle to support. Insurers operating on legacy foundations find themselves at a disadvantage when it comes to meeting these evolving regulatory requirements. This is because their siloed data structures and inflexible architectures make it difficult to aggregate the comprehensive metrics and evidence that regulators now demand. Meanwhile, their competitors use AI to personalise their offerings and improve statutory compliance.
Winning the insurance battle through experience
Modern insurance customers expect the same level of digital sophistication they experience with technology companies. They want instant quotes, seamless claims processing, and personalised coverage recommendations. These expectations cannot be met through incremental improvements to existing systems; they demand platform capabilities that legacy architectures were never designed to support.
New technology companies and insurtechs enter the market with cloud-native platforms and AI-first approaches, and aren’t restricted by legacy constraints. However, while these new entrants bring technological advantages, established insurers retain significant assets: brand trust, regulatory experience, and market scale. The challenge for traditional insurers is building on their reputable assets to encompass swift and sophisticated tech offerings.
Progressive modernisation strategies
Transformation demands bold innovation, balanced by smart risk. Rather than attempting wholesale system replacement, leading insurers should adopt incremental modernisation strategies that deliver continuous business value while reducing operational risk.
This typically begins with modern data capabilities that create a foundation for advanced analytics and AI deployments. By establishing cloud-based data platforms and API connectivity, insurers can start extracting value from their information assets while maintaining existing operational systems.
Microservices architectures are crucial in allowing insurers to decompose monolithic applications into manageable components that can be modernised independently. This approach cuts complexity and adds new capabilities without disrupting core operations.
Insurers need to rethink their software development processes. Traditional development cycles, often measured in months or years, can’t support the rapid iteration required in today’s competitive environment. Teams rely on DevOps, automated testing, and continuous integration to sustain innovation velocity and ensure system reliability.
The transformation extends to organisational structures as well. Successful modernisation requires breaking down silos between business and technology teams, creating cross-functional units that can respond quickly to market opportunities and customer needs.
Looking ahead
The 70% budget trap will only worsen with time, making transformation more expensive and disruptive as the delay continues. Successful modernisation is a comprehensive business strategy spanning the full operational stack, not a one-off tech project.
Companies that navigate this transition will emerge with platforms capable of supporting future innovations while turning their technical debt into a digital dividend that funds competitive advantage.
