What actually makes automated and enhanced underwriting work in practice?

In this episode, three early movers in automated underwriting share hard-earned lessons from building digital underwriting propositions that have survived real market cycles. Rather than theory or hype, this conversation digs into where technology genuinely creates advantage, where it does not, and how underwriting judgement remains central even in highly algorithmic models.

Drawing on experience across cyber, US property and digital facilities, the panel explores why complexity, not commoditisation, is often where automation delivers the greatest edge. From AI-driven cyber underwriting to high-cat surplus lines property and digitally distributed specialty products, each speaker explains how they chose their focus and what they learned along the way.

Key themes include the role of data discipline in sustaining AI-led underwriting, why platform design matters more than speed to market, and how underwriters’ roles are shifting from generalists to specialists embedded in algorithmic decision making. The discussion also tackles unstructured data, submission quality and why “no data, no deal” may become a defining principle of future underwriting models.

What you’ll learn in this episode:

Why complex risks can be better suited to automated and augmented underwriting than simple, commoditised ones
How AI and machine learning are being applied in live underwriting decisions, not just analytics
The importance of volume, homogeneity and risk differentiation when building algorithmic models
Lessons from re-platforming early digital products and avoiding long-term technical debt
How generative AI is changing data cleaning, exposure management and submission handling
What enhanced underwriting means for underwriter skills, careers and decision making

Featuring perspectives from Marek Shafer of Vave, Tom Squires of AEGIS London and Jonathan Spry of Envelop Risk, moderated by Matthew Grant of InsTech.

You can also watch the video version of this panel here.

If you like what you’re hearing, please leave us a review on whichever platform you use or contact Matthew Grant on LinkedIn.