A new report finds that hurricane risk models designed to predict insured losses in the U.S. from Atlantic hurricanes for the five-year period ending in 2010, significantly overestimated these losses for the cumulative 2006 through 2008 hurricane seasons.
The report was issued by Boston-based Karen Clark & Co., whose founder, Karen Clark, developed the first hurricane catastrophe model and in 1987 founded the first catastrophe modeling company, Applied Insurance Research (AIR).
Near term models were introduced in 2006 by the three major catastrophe modelers − AIR Worldwide (AIR), EQECAT and Risk Management Solutions (RMS). AIR initially predicted an overall annualized increase in hurricane losses of 40 percent above the long term average, but later lowered that figure to 16 percent in 2007. EQECAT predicted increases of between 35 and 37 percent, and RMS consistently predicted an overall increase of 40 percent above the long term average, the report says.
Assuming long term average annual hurricane losses of $10 billion for each year, these figures translate into cumulative insured losses for 2006 through 2008 of $37.2 billion, $40.8 billion, and $42 billion respectively, for the AIR, EQECAT and RMS models.
Thus, according to the report, the actual cumulative losses were $13.3 billion, far lower than the model predictions, and more than 50 percent below the long term cumulative average of $30 billion.
“With the close of the 2008 hurricane season, and three years into the application of near term hurricane models, it is a good time to evaluate the models’ performance,” said Clark, president and CEO of the consulting company that bears her name. “While it is still too early to make definitive conclusions about the near term models, with insured losses significantly below average for the cumulative 2006 through 2008 seasons, initial indications are there is too much uncertainty around year-to-year hurricane activity and insured losses to make credible short term predictions.”
Catastrophe models were introduced to the insurance industry in the late 1980s. By utilizing many decades of historical data, the models promised to give insurance companies better estimates of what could happen and more specifically, the probabilities of losses of different sizes on specific portfolios of insured properties. The destructive 2004 and 2005 hurricane seasons were catalysts for introducing the near term models. Use of these models by insurance and reinsurance companies, which are based on short term assessments of the frequencies of hurricanes, was a departure from the way in which catastrophe average annual losses (AALs) and probable maximum losses (PMLs) are typically derived.
According to the Karen Clark & Co. report, in order for insured losses to reach 40 percent above average for the five year period, in line with the highest model predictions, the next two years will have to be similar to 2004, or there will have to be another Hurricane Katrina.
The report notes that hurricane activity is influenced by many climatological factors, many of which are known, but some unknown, by scientists. There are complicated feedback mechanisms in the atmosphere that cannot be quantified precisely even by the most sophisticated and powerful climate models. The report recommends that insurers, reinsurers and regulators evaluate the efficacy of the near term hurricane models in light of this uncertainty.
“Standard, long term catastrophe models are characterized by a high degree of uncertainty, and short term assumptions on frequency and severity only magnify this uncertainty and the volatility in the loss estimates,” noted Clark. “While computer models are valuable decision-making tools, they can lead to bad business decisions when not used correctly. Model users frequently forget that all models are based on simplifying assumptions, and therefore all models are wrong. Models attempt to replicate reality, but they are not reality.”
The report, Near Term Hurricane Models – How Have They Performed?, is available at www.karenclarkandco.com.
Source: Karen Clark & Co.
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