Insurance pricing models can be powerful but too often, they operate like black holes: data goes in, but wisdom doesn’t come back out. In this session, Tim Stout explores how explainable AI helps insurers escape the “black box” trap - making models more transparent, decisions more trustworthy, and insights more exciting. You’ll see how leading teams are using explainability to uncover pricing opportunities. This talk is for pricing professionals who want to combine high performance with high clarity to gain wisdom.

This session is for anyone who has worked in pricing and is curious about the impact of reserving on their role in pricing. Isabelle will start off with development factors – is what you see really what you get? How could a deeper understanding of reserving’s goals lead you to make more accurate assumptions? Could we learn something from the way that reserving approach uncertainty in their analytics, and how could we better integrate a more long-term, holistic approach into our analysis? We have such a lot to learn from the way reserving thinks – so why not come along and find out more!