Insurance and reinsurance are generally priced on the basis of past claims experience. This approach has two key weaknesses. The first problem is the limited time span for which claims data is available. The second is that the past is not necessarily a reliable predictor of the future. For the first problem the general solution involves linking natural hazard information from outside of the insurance industry to claims data, and hence producing models for geographically rating primary insurance. For the second problem, theories about possible climate trends, demographic changes, etc., can be built into GIS-based models.