Insurance firms that offer natural-disaster insurance base their rates on available information. The benefits from collecting additional data and incorporating this information to improve parameter estimates of probability distributions that are used to characterize natural-disaster events can be determined by computing changes in premiums as a function of additional data. Specifically, the worth of data can be measured by changes in consumer's surplus (the widely applied measure of benefits to consumers used in benefit-cost analysis) brought about when the premiums are adjusted. In this paper, a formal model of the process for setting insurance rates is hypothesized in which the insurance firm sets rates so as to trade off penalties of overestimation and underestimation of expected damages estimated from currently available hydrologic data. A Bayesian preposterior analysis is performed which permits the determination of the expected benefits of collecting additional geophysical data by examining the changes in expected premium rates as a function of the longer record before the data are actually collected. An estimate of the expected benefits associated with collecting more data for the representative consumer is computed using an assumed demand function for insurance. In addition, a sensitivity analysis of expected benefits to changes in insurance demand and firm rate-setting procedures is carried out. From these results, conclusions are drawn regarding aggregate benefits to all flood insurance purchasers.