A recent decision by Florida insurance regulators to reject Risk Management Solutions' short-term catastrophe model illustrates the controversial nature of the science of prediction. Catastrophe modeling expert Tom Stone spoke with Claims' to shed light on the science behind the models, how recent catastrophes have affected them, and accusations that insurers manipulate models to unfairly raise rates.

How much science is there to predicting catastrophic losses?

A tremendous amount of science and engineering is associated with catastrophe loss modeling. To date, however, the models are based on statistical interpretation of data collected over the last 120 years or so. But information collected more than 50 years ago is often sparse, incomplete, and inaccurate, which makes statistical interpretation problematic. This leads to a significant amount of uncertainty in the meaning of those statistics and how they should be applied to predicting future catastrophes. In addition, the climate is in a constant state of change, so it may not be appropriate to assume what happened in the past will be repeated in the future. As the models evolve and more information is collected, data relevant to current conditions will be used to better predict near-term risk.