Risky Science Podcast

Risk Market News
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The Risky Science Podcast features conversations with scientists, insurers, investors, portfolio managers, and others about the evolving science of predicting and modeling risk across both natural and man-made perils.

  1. FEB 18

    Black Box Problems, Machine Judgment and the Rules Nobody's Written Yet With Daniel Schwarcz

    A conversation with Daniel Schwarcz, professor at the University of Minnesota Law School, where he teaches insurance law, contract law, tort law, and financial regulation and his academic work sits at the intersection of AI governance and insurance regulation. (00:00) - Introduction (00:17) - Guest background: From P&C attorney to insurance law professor (02:13) - AI in insurance today: back-office efficiency vs. underwriting and claims (10:06) - Is AI "locked and loaded" for underwriters and claims departments? (12:24) - The 50-state regulatory problem and its compounding complexity (22:05) - Catastrophe modeling and AI in property underwriting (30:19) - Why disclosure usually forestalls regulation rather than protecting consumers (38:40) - Schwarcz's proposed fix for shadow insurance (43:40) - "Obamacare for Homeowners Insurance": the case for insurance exchanges (48:56) - Five-year outlook: where is the insurance industry headed?

    53 min

  2. FEB 11

    AI Risk, Markets and Modeling the Unknown With Daniel Reti

    In this episode of the Risky Science Podcast we are joined by Danie Retil, co-founder of Exona Labs, a startup building AI risk modeling and quantification tools.

    42 min

  3. FEB 4

    Prediction Markets, Parametrics and Rethinking Weather Risk With Dr. Partick Brown

    For decades, insurers, reinsurers and energy companies have relied on models, parametrics, and traditional hedges to manage hurricane and weather exposure. But what if markets could continuously price those risks — in real time — and let anyone transfer or hedge them instantly? In this episode I’m joined by Dr. Patrick Brown, Head of Climate Analytics Interactive Brokers  to talk about modeling the models, forecast contracts, and whether prediction markets could become the next tool in the risk-transfer stack for the institutional market.

    54 min

  4. JAN 21

    Greenland, Venezuela and the New Political Risk Model Reality with WTW’s Sam Wilkin

    In this episode of the podcast, we speak with geopolitical risk expert Samuel Wilkin of Willis Towers Watson about why political risk is moving from a background concern to a front-line business problem. Sam breaks down the rise of “gray zone” attacks in the space between war and peace—from covert sabotage to infrastructure disruption—and explains why these threats are so difficult to model and insure. He also argues that the future of political risk management is less about perfect forecasts and more about scenario discipline, exposure mapping, and governance structures that can keep up with a faster, messier geopolitical cycle.

    47 min

  5. JAN 14

    Cyber Risk in 2026 and Why Near Misses Matter More Than Losses With Morgan Hervé-Mignucci

    In our first episode of the New Year we are focusing on cyber risk in 2026, a peril that looks increasingly systemic, yet remains poorly understood when it comes to how losses actually materialize. Over the past decade, cyber risk modeling has matured rapidly. But as cloud concentration deepens, dependencies multiply, and “near miss” events become more frequent, a central question remains unresolved: what does a truly systemic insured cyber loss actually look like—and are markets prepared for it? In this conversation with Coalion’s Dr. Morgan Hervé-Mignucci,Head of Risk Modeling at Coalition ,the discussion focuses on how cyber models have evolved, where they still fall short, and why many high-profile disruptions generate far less insured loss than the headlines suggest.

    42 min

  6. 12/24/2025

    Climate, Markets and the Limits of Insurability with Dave Jones

    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.

    52 min

  7. 12/17/2025

    Climate, Catastrophe Models and the Limits of Prediction with Dr. Roger Pielke Jr.

    Register for the January 8 Risky Science Podcast Live 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.

    42 min

  8. 12/10/2025

    Housing Prices, Climate Signals and Reinsurance Shocks with Dr. Philip Mulder

    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.

    50 min
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About

The Risky Science Podcast features conversations with scientists, insurers, investors, portfolio managers, and others about the evolving science of predicting and modeling risk across both natural and man-made perils.

Information

  • Creator
    Risk Market News
  • Years Active
    2025 - 2026
  • Episodes
    30
  • Rating
    Clean
  • Copyright
    © Parametric Publishing
  • Show Website
    Risky Science Podcast