A much higher fraction of the benefits of prediction markets are public goods.
Most forms of insurance did took a good deal of time and effort before they were widely accepted. It's unclear whether there's a dramatic difference in the rate of adoption of prediction markets compared to insurance.
Insurance exists for a specific reason. People buy insurance contracts because they want to hedge some kind of risk. Insurance companies can diversify this risk across many uncorrelated bets. With prediction markets neither of these is necessarily true, so you are not guaranteed to have positive-sum trades. Even when there are theoretically trades to be made, pricing contracts on random propositions with poor reference classes is much more difficult than forecasting the probability of death, earthquakes, a golf hole-in-one, etc., so it may not be worthwhile.
If people enjoy gambling on random propositions like the fate of the king's mistresses, that's an entirely different business model.
Insurance is very different from a prediction market. There are competitive aspects, but the wager is between a professional oddsmaker and a consumer. Price (aka probability) discovery in insurance is performed by experts, not by buyers of the insurance.
I wrote about exactly this recently- https://www.lesswrong.com/posts/zLnHk9udC28D34GBB/prediction-markets-aren-t-magic
Insurance is big business and is load-bearing for many industries. It has gained popular acceptance. Prediction markets have not. This is despite clear similarities between the two domains.
One can list similarities:
Or you can consider this extract from an official history of Lloyd's of London[1]:
So, given the many and obvious similarities between insurance markets and prediction markets, why have insurance markets succeeded where prediction markets have not?
Taken from pages 26-28 of Hazard Unlimited by Anthony Brown.