Given all of the uncertainties, near term projections do not have sufficient credibility to be used for important insurance applications such as product pricing and establishing solvency standards. In the case of pricing catastrophe exposure, the insurer or reinsurer is faced with the challenge of settling on a specific price for a specified time period for an exposure that has a highly uncertain expected value. While the near term models might be a useful tool for adding insight with respect to the potential range of expected outcomes for the upcoming policy period, the actual results of the last four years indicate that relying exclusively on the near term models to determine a rate can bring an extra level of instability and volatility to an already challenging pricing exercise. Individual insurers and reinsurers should instead consider the complete range and likelihood of possible outcomes in determining product pricing, taking into account the need for both stability and responsiveness in setting a strategy for pricing their products.The perspective expressed by Karen Clark and Co. is quite similar to my own views, expressed in a paper published in 2009. Our website remains down, due to a concerted attack to deny access, but for anyone interested I'd be happy to email a copy of the paper, the title and abstract appear below.
United States hurricane landfalls and damages: Can one- to five-year predictions beat climatology?Also, I participated in an AM Best roundtable discussion of catastrophe risk with insurance experts several weeks ago. The issue of catastrophe models was a part of the conversation. You can read a transcript of the discussion here. That is me below at the roundtable, talking about continued growth of losses based on our work.
Pielke, Roger A.
Environmental Hazards, Volume 8, Number 3, 2009 , pp. 187-200(14)
This paper asks whether one- to five-year predictions of United States hurricane landfalls and damages improve upon a baseline expectation derived from the climatological record. The paper argues that the large diversity of available predictions means that some predictions will improve upon climatology, but for decades if not longer it will be impossible to know whether these improvements were due to chance or actual skill. A review of efforts to predict hurricane landfalls and damage on timescales of one to five years does not lend much optimism to such efforts in any case. For decision makers, the recommendation is to use climatology as a baseline expectation and to clearly identify hedges away from this baseline, in order to clearly distinguish empirical from non-empirical justifications for judgements of risk.