What if your climate risk assessments could predict the future with greater accuracy than historical data alone?

In part two of this conversation on Making Risk Flow, Jake Harding continues his discussion with Joan Saladich, Founder of Geoskop, exploring how insurers can move beyond static climate risk models and embrace a more sophisticated, forward-looking approach to decision-making. Joan explains why annual climate model updates can create misleading conclusions, how vegetation and soil dynamics reshape wildfire risk, and why relying on single-source data leaves carriers exposed to blind spots. 

The conversation also examines the role of AI and large language models in processing complex climate datasets, emphasising that technology should enhance, not replace, human judgment. Joan outlines a practical framework for combining historical data, future climate projections, alternative statistical models, and socioeconomic context to generate more accurate, explainable, and actionable climate risk intelligence. 

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Our previous guests include: Bronek Masojada of PPL, Craig Knightly of Inigo, Andrew Horton of QBE Insurance, Simon McGinn of Allianz, Stephane Flaquet of Hiscox, Matthew Grant of InsTech, Paul Brand of Convex, Paolo Cuomo of Gallagher Re, and Thierry Daucourt of AXA.

Check out the three most downloaded episodes:

• The Five Pillars of Data Analytics Strategy in Insurance | Craig Knightly, Inigo
• 20 Years as CEO of Hiscox: Personal Reflections and the Evolution of PPL | Bronek Masojada
• Implementing ESG in the Insurance and Underwriting Space | Simon Tighe, Chaucer, and Paul McCarney, Moody's