Aviva

Aviva underwriters processing individual critical illness and life insurance applications faced a significant bottleneck at the front end of the underwriting journey: manually reading and interpreting lengthy, complex medical reports before making coverage decisions. These reports — often dense clinical documents covering a customer's full medical history — required substantial time to parse for the specific details relevant to a given application. The cumulative drag on throughput slowed turnaround times for customers and advisers alike, and constrained the volume of protection applications underwriters could handle. In a market where speed-to-decision directly affects both customer experience and the accessibility of protection products, this manual review burden represented a measurable competitive and operational liability.

Aviva built and deployed a generative AI summarisation tool designed specifically for the protection underwriting workflow. The system ingests full medical reports and distills them into concise, decision-relevant summaries — surfacing only the clinical details an underwriter needs to assess a given application. Rather than a single large-scale rollout, Aviva adopted a phased expansion strategy: the tool launched for individual life insurance applications in November 2025, then extended to critical illness (CI) cover in March 2026, bringing it to the majority of individual protection cases requiring a medical report. The tool integrates into the existing underwriting workflow rather than replacing underwriter judgement — it handles information distillation while the underwriter retains full decision-making authority. The capability has also been extended to post-application auditing, with income protection summarisation identified as the next phase.

The AI summarisation tool has delivered a roughly 50% reduction in the time underwriters spend reviewing each case — a substantial efficiency gain across a high-volume workflow. Aviva positions both the original launch and the CI expansion as industry firsts in the UK protection market, indicating no comparable tool was previously available at this stage of the underwriting process. Qualitative outcomes include improved turnaround times for customers seeking coverage decisions and better service levels for financial advisers managing client applications. The phased rollout also validates the approach without requiring a wholesale process change:

• ~50% reduction in per-case underwriter review time
• Coverage across most individual protection applications requiring a medical report
• Extended to post-application auditing beyond initial underwriting use

• Deploying AI at the information-preparation layer — rather than the decision layer — allows measurable efficiency gains while keeping underwriters in control of risk decisions, reducing regulatory and governance friction.
• A phased product-line rollout (life → CI → income protection) lets teams validate performance, build internal confidence, and manage risk before committing to full-scale deployment.
• AI summarisation tools in protection underwriting create compounding value: faster underwriter throughput, better adviser service, and improved customer access to coverage — three stakeholder groups improved by a single capability.
• Early movers claiming industry firsts in AI-assisted underwriting may gain disproportionate operational and reputational advantages before market standardisation sets in.