The conversation around AI in underwriting is shifting, from what’s possible to what’s already in play. This webinar offers a practical look at how AI tools are embedded into underwriting environments, transforming how risks are assessed, decisions are supported, and data is utilised.
Featuring insights from insurers, product teams, and underwriters who work with these systems daily, the session will explore what’s delivering value, where challenges persist, and how expectations around performance and capability are evolving. Focusing on applied use cases, this discussion moves beyond theory and into operational reality.
What real-world problems is AI solving in underwriting today, from triage and submission scoring to data enrichment and decision support?
Where has AI delivered measurable improvements in underwriting performance, such as reducing manual workload, increasing consistency, or improving risk selection?
What practical barriers have emerged during deployment, including issues around integration, data quality, adoption, and internal trust in AI outputs?
How are underwriters working alongside AI tools in day-to-day workflows, combining human judgment with machine-driven insight?
What lessons have early adopters learned about scaling AI responsibly, particularly around governance, feedback loops, and ensuring explainability?
The challenges being faced by underwriting teams and avoiding potential pitfalls
