UnderwriteMe has today announced the launch of AI Engine for post-issue audits, an automated misrepresentation detection solution designed to help life insurers expand audit coverage without increasing underwriting resources.
Post-issue audits are reviews conducted after a life insurance policy has been issued to compare the information provided in the application with medical records or other evidence. When done well, they help insurers identify inaccuracies before a claim occurs, allowing issues to be addressed earlier. This gives customers and advisers further peace of mind, while strengthening pricing integrity and confidence in the insurer’s overall risk portfolio.
Post-issue audits also play an important role in maintaining pricing accuracy and portfolio integrity. By comparing application disclosures with medical evidence obtained after policy issuance, such as GP reports or medical records, insurers can validate that underwriting decisions and pricing assumptions were based on complete and accurate information.
A robust post-issue audit programme helps insurers to detect any discrepancies or misrepresentations on an application, helping to maintain consistent underwriting standards, protecting pricing integrity and ensuring fair outcomes across policies. For advisers, this strengthens confidence that accurately disclosed applications will be treated fairly and reduces the risk of disputes or surprises at claim time.
In traditional audit processes, underwriters must manually review medical documentation to identify potential discrepancies. As a result, many insurers audit only a small proportion of issued policies, limiting the scale at which audit programmes can support governance, pricing oversight, and reinsurer reporting.
AI Engine automates misrepresentation detection, with the aim of significantly reducing underwriter review time on clean and flagged cases. In beta testing with four major UK life insurers, AI Engine demonstrated a 98% misrepresentation detection rate, a 75% reduction in underwriter review time on clean cases (no misrepresentation detected), and a >50% reduction in review time on flagged cases (misrepresentation detected).
For flagged cases, AI Engine automatically links every misrepresentation finding to the precise location in the source medical evidence to help make outcomes traceable and defensible to regulators and reinsurers.
AI Engine integrates into existing underwriting workflows, aligning with internal AI governance, model risk, and data protection requirements, including automated anonymisation of medical documents.
The AI functions as a decision-support tool, with final accountability for misrepresentation determinations remaining with human underwriters.
"Post-issue audit is an important component of pricing governance for life insurers," said Andy Doran, CEO of UnderwriteMe. "AI Engine allows insurers to move from constrained sampling to scalable, consistent audit oversight, strengthening portfolio integrity without increasing operational burden.
"Working in partnership with our beta programme customers was central to how AI Engine was developed. Their underwriting teams worked closely with ours to test the solution in real audit workflows and challenge how misrepresentation detection should operate in practice. That collaboration helped us refine AI Engine, so it reflects real underwriting judgment, aligns with each insurer’s philosophy, and delivers the transparency and traceability required for confident audit decisions."
