Instech London Podcast

What does it take to build a wildfire prediction model that not only outperforms physics-based approaches but also fits seamlessly into underwriting? In this episode, Matthew Grant is joined by Sarah Russell, General Manager at Bellwether – a climate-focused moonshot from Google X – to explore why wildfires are the ideal proving ground for next-generation insurance analytics.  This isn’t, however, just another conversation about AI potential. Sarah explains why wildfire risk fits machine learning better than traditional methods, how Bellwether is helping insurers find overlooked low-risk zones and why explainability, not black-box brilliance, is key to adoption. She also shares what’s next – from agentic AI to Severe Convective Storm models – and what the industry needs to be ready for. Key Talking Points: Wildfires as a moonshot – why Bellwether started with wildfire risk to build a prediction engine for the Earth From physics to AI – how machine learning outperforms traditional models in dynamic, data-heav