Short-Term Models Continue to Disappoint: Clark

Short-term hurricane models have proven to be inadequate tools for insurers looking to measure loss exposure over the past decade, according to a report released Tuesday by Boston-based Karen Clark & Co.

In fact, firm president Karen Clark argues that short-term models issued by AIR, EQECAT and RMS have overestimated insured losses by tens-of-billions over the past several years and cut into insurer profitability.

“Now that we have completed the first five-year near term hurricane model projected period, it has become clear, as our previous reports have found, that a short time horizon is not sufficient for credibly estimating insured losses from hurricanes,” Clark says in a statement. “Tropical cyclone activity changes markedly year to year, and even a near-record season of storm activity such as 2010 does not necessarily translate into large insured losses.”

According to the latest near term hurricane models performance report, Clark says that actual cumulative insured hurricane losses were only $15.2 billion — significantly lower than modeling firm predictions of between $60.4 billion and $68.2 billion, and less than one-third of the long-term cumulative average of $50 billion.

Clark attributes the difference to the Hurricane Frequency Paradox, which says that while there has been an increase in Atlantic tropical activity since late 19th century there is no corresponding increase in hurricane landfalls in the United States. The report states that the percentage of storms making landfall has declined to 60 percent, compared to an average of about 75 percent prior to 1965.

“While most scientific research focuses on the number of storms that develop, insurance companies are most interested in landfalling hurricanes that cause significant losses, so the hurricane frequency paradox is an important issue for the industry,” Clark says in the statement. “There is simply no clear basis for concluding we are in a period when losses associated with hurricanes should be expected to be well above the long term average.”


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