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.
We're joined by Dr. Paolo Bocchini, Professor of Civil and Environmental Engineering at Lehigh University, a leading researcher in catastrophe modeling and infrastructure resilience. Dr. Bocchini is the director of Lehigh’s Center for Catastrophe Modeling and Resilience, and he’s spearheading a new collaboration with Rice University—the Consortium for Enhanced Resilience and Catastrophe Modeling.
In this episode, we dive into why academic and private-sector research in catastrophe risk have grown apart—and what it takes to reconnect them. We talk about multi-hazard risk, the power and limits of AI in modeling, the role of surrogate models, and how future disasters—from wildfires to earthquakes—demand new thinking.
In this episode of the podcast, we are shifting from modeling physical risks to exploring how wargaming and combat modeling is being used to understand the growing threat of geopolitical conflict.
Our guest is Dr. Jeremy Sepinsky, Lead Wargame Designer at CNA, a federally funded research and development center that supports national security analysis.
We dive deep into how wargaming differs from traditional combat modeling, how escalation and de-escalation decisions are captured through human dynamics, and what all of this means in the context of current tensions with Iran.
Whether it’s simulating natural disasters, cyber warfare to strategic miscommunication, Dr. Sepinsky explains how wargames help reveal the unpredictable—but actionable—dimensions of risk that quantitative models alone can’t capture.
In this episode of the Risky Science Podcast, Dickie Whitaker, CEO of the Oasis Loss Modelling Framework, discusses how open-source catastrophe modeling is transforming the risk ecosystem. Whitaker shares the origin story of Oasis and how the platform is working to lower barriers to entry, spur innovation, and increase transparency in a space long dominated by proprietary models. The conversation covers how Oasis has evolved over the past decade, recent milestones in its adoption by major players like Moody’s and Verisk, and the importance of model evaluation frameworks in ensuring trust and credibility—especially for regulators, reinsurers, and developing countries.
Whitaker also offers a behind-the-scenes look at Oasis’s technology roadmap, including performance upgrades for large portfolios, growing support for cyber and climate-conditioned models, and new tools tailored for low-resource environments. From global reinsurers to national risk pools, the episode explores the expanding use cases for open modeling and what success looks like for an ecosystem built on collaboration. Whether you're a model developer, regulator, or insurance professional, this episode offers a candid look at the future of catastrophe risk analytics.
As insurers seek higher yields in a persistent high-rate environment, private credit has become an increasingly significant part of portfolio strategies. But with that growth comes a new set of questions—about liquidity, transparency, and the long-term implications for credit quality. Carmi Margalit shares S&P’s analytical framework for assessing these risks, highlighting what insurers, regulators, and investors should be watching.
After a long hiatus, we’re back—launching a new series of conversations with finance professionals, academic researchers, and technology leaders focused on a rapidly growing and often misunderstood area of risk: modeling.
In this episode, we kick things off with a conversation about weather and climate modeling with Dr. Daniel Swain, a climate scientist at the University of California Agriculture and Natural Resources and the National Center for Atmospheric Research. Daniel is best known for his work on extreme weather events, climate change communication, and for developing the "weather whiplash" framework to describe rapid shifts between extremes. He’s also the voice behind the widely followed Weather West blog.
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