In the last episode of Risky Science, we examined skepticism around climate-conditioned catastrophe models with Roger Pielke Jr.—questioning how much weight long-range climate assumptions should carry in near-term insurance and capital decisions.
Today’s discussion is a direct counterpoint.
My guest is Dave Jones, former California Insurance Commissioner and now director of the Climate Risk Initiative at UC Berkeley Law. His recent article argues that insurance itself has become the clearest early-warning signal of climate risk—describing property insurance as the “canary in the coal mine,” and warning that the canary is already dying.
This conversation is timely because the stress is no longer theoretical. Catastrophe losses are accelerating, insurers are pulling back from high-risk regions, and residual markets are expanding rapidly. Jones argues that neither deregulation nor rate increases will be enough if the underlying drivers of loss continue to intensify.
We’ll examine California and Florida as live case studies, what mitigation and modeling can realistically achieve in the near term, and where the practical limits of insurance may already be coming into view.
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In this episode, I’m joined by Roger Pielke Jr., a researcher known for his work on the use—and misuse—of models in risk and policy decisions. Pielke is a polarizing figure in climate research, particularly for his views on how climate change should—and should not—be incorporated into catastrophe models used for annual insurance and reinsurance decisions.
It was a timely conversation, especially as Pielke has recently used his Substack, The Honest Broker, to critique the current state of climate-risk analytics and modeling. Whatever your view of his conclusions, they offer a challenging and well-informed perspective on how risk models are being used today.
Register here for the January 8 Risky Science Podcast Live
This week on the Risky Science Podcast, I’m joined by Dr. Phillip Mulder of the University of Wisconsin, co-author of a newly released research paper examining how these insurance pressures are influencing who buys, who moves, and who can no longer afford to stay.
The research has drawn significant attention, including coverage in The New York Times. Dr. Mulder explains how one of the primary underlying forces in this emerging economic crisis is a series of “reinsurance shocks” — repricing events driven in part by catastrophe model estimates that are reverberating throughout the U.S. economy.
Our guest is Tim Boyce of TP ICAP, who has spent more than 25 years in financial markets, from US-dollar swaps in London to commodities in Singapore, before returning to the UK to build out the firm’s European weather business.
Tim describes weather as a “sleeping giant,” a market that should be much bigger given how energy, logistics, agriculture, and retail all rely on predictable weather and stable demand
We’ll talk about where demand is growing fastest, how better forecasting and satellite data are transforming hedging strategies, and why Tim sees weather derivatives and insurance as part of the same risk ecosystem — working together to get businesses the protection they need.
On today’s episode of the Risky Science Podcast, we’re stepping outside the usual finance lens and into a conversation that will push many of your assumptions about how risk, capital, and human health actually interact. Dr. Susan Erikson: medical anthropologist and author of Investable!, brings a perspective that most risk and financial professionals rarely engage with, but absolutely need to hear. Her work on pandemic bonds and the financialization of global health doesn’t just critique the structures we use; it forces us to rethink what “risk transfer” can and can’t solve when the underlying asset is human wellbeing.
China was once seen as a vast, untapped frontier for global risk finance — drawing interest from New York to London. Yet a combination of geopolitical headwinds and trade tensions has cooled expansion plans for many executives hoping to grow their Asian footprint.
That hasn’t stopped real innovation — especially in weather and physical-risk finance, where the market potential is becoming increasingly difficult to ignore.
In this episode, we speak with Jim Huang, founder of climateHedge, a firm with operations in both the U.S. and Shanghai. With a background in product strategy at the CME Group and a deep passion for opening Asian markets to weather-derivative trading, Jim is on a mission to educate the Chinese market. We discuss his on-the-ground progress so far — and how he sees weather derivatives, insurance, and reinsurance products evolving over the next decade.
Risk Market Briefing: Inside China’s Bid to Industrialize Weather Risk Trading
This week I’m joined by Meyer Shields of KBW, one of the most followed insurance analysts on Wall Street. We get into what’s driving that split, how AI and modeling are — or aren’t — starting to show up in real financial performance, and whether today’s property catastrophe discipline is a genuine structural reset or just another hard market waiting to unwind.
This week’s guest is Dr. Hansi Singh, an Earth system scientist who’s worked at the U.S. Department of Energy, taught in academia, and now leads a startup called Plannette.AI, which blends physics and AI to deliver long-range weather forecasts for industries including finance and insurance.
In this conversation, Dr. Singh explains why AI’s biggest weather-forecasting success have been within the seven-day window—and why pushing beyond that horizon remains so hard. We explore how AI can enhance—not replace—traditional physics-based models.
We also get into the practical side: how finance, insurance, and even energy traders are using AI-driven forecasts, what the rise of AI agents means for accessibility, and why transparency and back-testing are critical to overcome the industry’s skepticism toward “black-box” models.
Dr. Paul Wilson, Head of Catastrophe and Climate Research at Twelve Securis, a leading insurance-linked securities asset manager, sits down for a live recording of the Risky Science Podcast.
We sit down with Dr. Seth Baum, Executive Director of the Global Catastrophic Risk Institute and research affiliate at Cambridge University’s Centre for the Study of Existential Risk. We explore how societies understand and prepare for global-scale threats—from climate change and pandemics to nuclear conflict and artificial intelligence. Dr. Baum explains why uncertainty is the defining feature of catastrophic risk, why markets struggle to price the unthinkable, and why collective action and governance are essential to tackling the crises that no private market can solve.
Join the Risky Science Podcast for a live discussion with Dr. Paul Wilson, Tuesday, September 23, 11 a.m. ET.
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We speak with Dirk Schmelzer, Partner at Plenum Investments in Zurich. Dirk has spent more than 15 years managing catastrophe bond and insurance-linked securities funds, and he brings a practitioner’s perspective on how catastrophe models are actually used in portfolio management and investment decisions.
We’ll explore how models have evolved, where they still fall short, and how issues like climate change and artificial intelligence are reshaping the conversation.
This week we speak with Karen Clark, founder of Karen Clark & Company, about the evolution of catastrophe modeling and the shift toward higher-frequency, climate-driven events.
John Seo, founder of Fermat Capital, about the lessons of Katrina for catastrophe bonds and models 20 years later.
Less than a year after the devastating Los Angeles fires, I’m joined by Michael Wara from Stanford University.
We explore why Michael is skeptical about California developing a public wildfire model, despite being part of the strategy group that studied it. We'll dig into how the newly approved private wildfire models are about to transform California's insurance market. And we'll discuss something that's crucial but often overlooked: how community-scale risk mitigation efforts can and should be integrated into these models.
We talk with Dr. Victor Gensini, a professor at Northern Illinois University and one of the leading experts on severe convective storms. Dr. Gensini works with the Insurance Information Institute and has just launched a new center for convective storm research, bringing together academic research and industry needs to tackle this modeling challenge.
We'll explore why these storms are so much harder to model than hurricanes, what new data sources are filling the gaps in our understanding, and why we're still five to ten years away from having reliable catastrophe models for severe convective storms.
In this episode we talk with Dr. Tina Dura, a coastal hazard researcher at Virginia Tech, as she unpacks a threat that most risk models still underestimate: Sudden land subsidence from a long expected Cascadia subduction zone earthquake.
We're joined by Michiel W. Ingels, lead author of research that takes stock of the state of climate risk insurance modeling and maps out where it needs to go next.
On this episode of the Risky Science Podcast, we talk with Cory Isaacson, CEO of ReThought Insurance — a longtime tech and insurance executive who’s spent years building new models aimed at making flood risk more accurate, more transparent, and more insurable.
In this episode we speak with Dr. Neil Ferguson, a leading voice in infectious disease modeling and Director of the Jameel Institute at Imperial College London. We talk about how disease models are built, how they’ve evolved over the last two decades, and what happens when they move from academic research into policy, politics, and even the private sector.