In recent years, US policy makers have faced persistent calls for the price of flood and hurricane insurance cover to reflect the true or real risk. The appeal to a true or real measure of risk is rooted in two assumptions. First, scientific research can provide an accurate measure of risk. Second, this information can and should dictate decision-making about the cost of insurance. As a result, contemporary disputes over the cost of catastrophe insurance coverage, hurricane risk being a prime example, become technical battles over estimating risk. Using examples from the Florida hurricane rate-making decision context, we provide a quantitative investigation of the integrity of these two assumptions. We argue that catastrophe models are politically stylized views of the intractable scientific problem of precise characterization of hurricane risk. Faced with many conflicting scientific theories, model theorists use choice and preference for outcomes to develop a model. Models therefore come to include political positions on relevant knowledge and the risk that society ought to manage. Earnest consideration of model capabilities and inherent uncertainties may help evolve public debate from one focused on "true" or "real" measures of risk, of which there are many, toward one of improved understanding and management of insurance regimes.