Hear from three leading experts in natural catastrophe modeling, as we explore how climate change is causing the insurance industry to rethink their approach to modeling extreme weather.

In the previous episode, we discussed the challenges facing the insurance industry from climate change – so in this episode, we're going to dive into some of the solutions.

Since natural catastrophe (Nat Cat) modeling was established in the late 1980s, the predictive power of their models has come from the statistical analysis of historical data. But as climate change continues to push the frequency and severity of extreme weather into uncharted territory, this approach begins to lose some of its potency.

In response to this, new ways of thinking about Nat Cat modeling and insurance have emerged, with a focus on better capturing the effects of the changing climate on extreme weather. In this episode, we'll explore:

• The power of incorporating physics into the traditional Nat Cat modeling process;
• The recent explosion of earth system data and the role of machine learning in harnessing it; and
• How improved Nat Cat modelling can support innovative products, like parametric insurance, and what this means for closing the insurance gap.

To find out more about the Sustainability and Climate Risk (SCR®) Certificate, follow this link: https://www.garp.org/scr

For more information on climate risk, visit GARP's Global Sustainability and Climate Risk Resource Center: https://www.garp.org/sustainability-climate

If you have any questions, thoughts, or feedback regarding this podcast series, we would love to hear from you at: [email protected]

Links from today's discussion:

• Reask's Tropical Cyclone Database: https://journals.ametsoc.org/view/journals/mwre/152/1/MWR-D-22-0317.1.xml
• Reask's Tropical Cyclone Wind Model: https://journals.ametsoc.org/view/journals/mwre/145/8/mwr-d-16-0429.1.xml?rskey=9h0SUA&result=2
• Reask's Tropical Cyclone Rain Model: https://journals.ametsoc.org/search?f_0=author&q_0=Thomas+Loridan

Speaker's Bio(s)

Jamie Rodney, CEO, Reask

Jamie Rodney is the CEO of Reask, specializing in extreme weather risk modeling and forecasting. Jamie has over a decade of experience in applying advances in extreme weather analytics to the financial and reinsurance sectors. Jamie is dedicated to leveraging advanced technologies to enhance global climate risk understanding and support organizations in navigating complex climate challenges. Based in Zurich, he leads Reask's pioneering vision in developing a new class of extreme weather risk measurement capabilities that do not exist today. Jamie holds a PhD in Mathematics from University College London.

Thomas Loridan, Co-Founder and Chief Science Officer, Reask

Thomas Loridan is Co-founder and Chief Science Officer at Reask, where he leads the development of cutting-edge natural catastrophe models using machine learning to quantify global climate risk. Holding a PhD in Boundary Layer Meteorology from King's College London (2011), Thomas has deep expertise in atmospheric sciences and computational modeling. His work includes the creation of advanced wind field models for tropical cyclones and the integration of high-resolution data into probabilistic frameworks.

David Schmid, Head of Global Data Product, Reask

David Schmid is the Global Head of Data Products at Reask, where he oversees the development of products for risk assessment, parametric insurance and early warning systems. With over 15 years of experience in natural catastrophe risk modelling and parametric insurance, David has held roles at Glacier Re, NewRe, and Munich Re Capital Partners, where he contributed to advancing risk assessment and pricing standards. At Reask, David remains committed to developing innovative solutions that address the evolving needs of policyholders, brokers, and risk carriers.