Show Notes
Better cat modelling isn't just about avoiding bad risk, it's about finding and writing the good risk your competitors are mispricing. James Rendell, CEO of BirdsEyeView, saw that gap and convinced the European Space Agency to back him, and built something that the big vendors hadn't properly tackled. WHAT YOU'LL LEARN:- Why secondary perils like wildfire and severe convective storms are fundamentally harder to model than hurricanes — and how to tackle that properly- How year-old fuel data makes most wildfire models quietly unreliable, and what it means for your next renewal- Why a higher-resolution cat model is a revenue tool, not just a risk-avoidance one — and how soft market conditions make this more urgent- The meaningful difference between physics-based machine learning models and LLMs when you need to explain your risk view to an actuary- How an ESA-backed startup went from contingency market niche to a cat modelling platform used across Lloyd's syndicates, Australian cover holders, US MGAs and beyondTIMESTAMPS:00:00 James Rendell: from broker to insurtech founder01:54 BirdsEyeView and the ESA05:34 The cat modelling landscape07:00 The contingency market gap09:30 Why secondary perils are harder to model12:35 Wildfire, SCS, and building better models14:10 Physics, machine learning, and satellite data16:06 The fuel data problem18:00 AI and the future of cat modelling21:50 Soft market advantage: write more premium
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