Prediction Markets for Insurance is a use case I keep coming back to. They solve a core inefficiency; namely, the fact that cost and utilization (risk) rise and fall unpredictably. A weather event or flu outbreak spikes risk as an example. Many insurance providers price risk, but many industries like healthcare as an example have inflation that is endogenous. This comes from utilization patterns, pricing codes, and clinical behavior. These markets behave nothing like CPI (Consumer Price Index) or PCE (Personal Consumption Expenditures). Yet healthcare costs on insurance drives 17.6% of U.S. GDP. No market today lets anyone hedge that slope directly. Forecasts don't absorb risk; markets do. Until there’s a liquid instrument through a prediction market (@Kalshi, @Polymarket, etc), all insurance forecasting just shifts blame for misses. They don’t solve the underlying volatility.