By Jonathan Phillips, Life and Protection Lead, EIS
The existing model suited an era when growth was stable, policy triggers predictable, and customer expectations modest. But those conditions no longer hold. Growth in the life market is low, social and demographic trends are reshaping when and how people make major life decisions, and regulators are raising the bar on what counts as fair value and good outcomes. In this new environment, insurers who continue to treat annual statements as a compliance exercise risk missing a much larger opportunity: to use AI and data to reconnect with customers, anticipate their needs, and turn protection from a static product into a dynamic and continually relevant service.
A Market Under Pressure
The traditional drivers of life insurance purchases - marriage, home ownership, starting a family - are happening later, less frequently, or not at all. Younger generations, in particular, are delaying or rethinking milestones that would once have triggered protection needs. At the same time, persistently low growth in the sector means insurers must work harder to expand coverage and build loyalty among existing customers.
Overlay this with a challenging regulatory climate. The UK’s Consumer Duty, introduced by the FCA, requires insurers to deliver fair value and proactive engagement. That means moving beyond the bare minimum of annual statements to demonstrate that products remain suitable and customers are getting the protection they are paying for. The question is no longer whether insurers should engage more actively, but how.
Organised Around Policies, Not People
One of the biggest obstacles to meaningful engagement lies in how insurers are organised. Most life companies are structured around policies rather than customers. That logic made sense when administration was paper-based, and the policy was the unit of record. But it creates problems in a digital world where the customer expects their provider to know them as an individual, not as a set of disconnected contracts.
The effect is magnified by legacy systems. Operational and customer data often sits in silos, split by product line, channel, departmentalised functions or business unit. Without a single customer ID that links these fragments together, it is impossible to build a coherent picture of the policyholder’s life journey. And without that picture, even the most advanced AI tools cannot generate insights that drive better experiences or stronger commercial outcomes.
The AI Opportunity…turning data into knowledge and action
AI has enormous potential to reshape life insurance, but only if it can interact with data that is complete, consistent, and connected. When that foundation is missing, AI delivers little more than surface-level automation, and the initial focus of many insurers has been efficiency (doing the same faster) and not customer relevance or experience.
When the foundation is present, however, the possibilities multiply:
Proactively Detect Life Events: With access to financial, behavioural, or third-party data (via open banking, for instance), AI can identify signals that a customer’s circumstances are changing—moving house, having a child, or approaching retirement. Rather than waiting for the customer to initiate contact, the insurer can proactively suggest relevant adjustments.
Turn Static Touchpoints into Dynamic Engagement: AI-powered assistants can transform static annual statements into interactive prompts. Instead of a letter that goes unread, customers receive personalised nudges, delivered through digital channels they actually use, that make it easy to ask questions or update coverage.
Deliver Personalised risk and Coverage Insights: By combining customer data with broader demographic and economic trends, AI can help insurers offer advice on optimising coverage, reducing risk exposure, or adjusting premiums in ways that benefit both customer and insurer.
Seamless third-party integration: By connecting to external data sources through open banking or other APIs, insurers can enrich their understanding of customers’ lives and tailor offerings with greater precision.
Each of these examples shows that AI alone isn’t the solution. i. It’s true value comes when it breaks free from legacy silos and embeds into the core, transforming automation at the surface into impact at the heart of the business.
Annual Statements as a Test Case
Annual statements illustrate both the challenge and the opportunity. Historically, many insurers avoided drawing attention to policies, fearing that questions or requests would expose their inability to adapt coverage. Yet when one UK insurer recently took the opposite approach - proactively reminding policyholders about their coverage - it uncovered and paid retrospective claims worth millions.
Now imagine that process powered by AI - detecting risks, tailoring outreach, and engaging customers in real time. Compliance moves from a cost-centre to a driver of loyalty, revenue, and trust.
The opportunity - From Reactive Compliance to Anticipatory Service
Most insurers today remain stuck in reactive compliance. They meet regulatory requirements, but they do so in ways that satisfy the letter rather than the spirit of Consumer Duty. The result is a customer relationship that remains largely passive. The firms that will lead the next phase of the market are those that reorganise around the customer, unify their data, and deploy AI to anticipate rather than react. The commercial benefits are compelling:
Increased retention and loyalty, as customers feel more connected to and understood by their insurer.
Greater revenue per customer, as engagement opens opportunities to provide new services and adjust coverage in line with life changes.
Reduced risk exposure, as insurers can better match products to actual customer circumstances.
Enhanced trust and reputation, as proactive engagement demonstrates genuine commitment to protection.
Reimagining the Customer Relationship
To reframe life insurance as a dynamic, lifelong service rather than a static contract, insurers must do more than modernise technology. They must rethink their organisational models, moving from policy-centric structures to customer-centric services. AI can then act as the catalyst, connecting disparate information, surfacing relevant insights, and enabling timely, personalised engagement. In doing so, it helps insurers meet their regulatory obligations while turning compliance into competitive advantage. The opportunity is clear: turn annual statements into lifelong conversations, compliance into competitive advantage, and static products into dynamic services. For a sector long constrained by legacy structures and limited growth, that shift could be transformative.
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