Insurance Uncut: GIRO 2025
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In this special mini-series, Jess and Charl are recording from the annual GIRO conference 2025 in Liverpool. The interview a range of special guests from around the insurance industry and conference speakers.
Capital modelling and validation market review
We caught up with Cat Drummond and Tom Durkin about their presentations on capital modelling and validation market review: Industry trends and best practices.
IFoA Climate Sensitivity Working Party
Next, we speak to James Orr and Oliver Bettis from the IFoA Climate Sensitivity Working Party to discuss there latest research on climate sensitivity, which looks at why we should we care and what can we do if it’s more than we thought?
More data or more model
As part of the GIRO 2025 mini-series, we speak to Gwen Chan on: “more data or more model? - a framework for achieving predictive analytics objectives in specialty insurance”. Gwen’s and Priyank’s research is looking to measure the predictiveness of different datasets.
Electric vehicles
As part of the GIRO 2025 mini-series, we speak to Amit Parmar about electric vehicles. We discuss the research Amit and Conor Woods have done on whether electric vehicles crash more or less than petrol cars.
Autonomous vehicles
As part of the GIRO 2025 mini-series, we speak to Chris Jones, Doug Woodley and Yousif Al-Ani about the latest on Autonomous Vehicles (AVs). We cover: when will we see AVs on UK streets, how will insurance work and who are the key players in development of AVs?
Its all about pricing actuaries
As part of the GIRO 2025 mini-series, we speak to Catrin Townsend about Price Writers, Catrin’s book “A Risky Business” and how we need smarter governance for smarter pricing models.
President of the IFoA
We speak to Paul Sweeting about what his aims are for his presidency and what he sees as the future for the insurance profession.
Emerging risks, linking up Capital and Pricing
Isabelle Williams and Richard Holloway from LCP walk us through their session on how pricing and capital teams can work better together to stay ahead of emerging risks.
UK Flood Insurance
Richard Stock and Tom Saliba from the Flood Working Party share their view on how to work with government and stakeholders to build a more sustainable approach to UK flood risk.
Interpretable Boosted GLM
We speak to Karol Gawlowski and Patricia Wang from the IFoA Actuarial Data Science Working Party talk us through their Brian Hay Prize winning research on Interpretable Boosted GLM.
Insurance Uncut at GIRO 2025 - day 3
Claims inflation
On day 3 we hear from Cian Creedon and Marcus Schofield from the Claims Inflation Working Party. We discuss the results from their inflation survey and how expectations for future inflation will vary by line business going forward.
Foundational machine learning climate models
Debashish Dey joins us to share research that blends climate change and AI. He talks through his latest work and his career path.
Fighting for Python
George Wright talks about the tools and support actuaries need for modern modelling.
Actuaries at an AI crossroads: Is your AI policy leading you in the right direction?
Geraldine Finucane and Hazel Davis from the Professionalism, Regulation and Ethics working party explain what good governance looks like in practice and how to judge whether your firm has the right oversight in place.
Martin Assmann
Martin Assmann from Insurance ERM joins us to share the stories they are covering right now.
A new approach to reserve risk
Ahead of GIRO 2025, we talk to Lara Palmer and Jade Lagrue from LCP about their new research on modelling reserve risk, exploring the limitations of current approaches, their analysis, and the potential applications and next steps.
This podcast is for information purposes only and should not be taken as advice. All views expressed by podcast hosts and guests are purely their own opinions and do not represent those of LCP, its clients or affiliates. LCP makes no warranty, guarantee, or representation as to the accuracy or sufficiency of the information featured in this Podcast.
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