Karen Clark & Company Executive Briefing to Provide Guidance on Use of New U.S. Earthquake Models
BOSTON, MA, September 14, 2009
Karen Clark & Company, independent experts in catastrophe risk, catastrophe models, and catastrophe risk management, today announced a new Executive Briefing, “Implementing the New U.S. Earthquake Models: Look Before You Leap.” This one-and-a-half hour briefing, designed specifically for boards of directors and insurance company senior executives, provides guidance on how to interpret and use the new models.
In early August, the two major catastrophe modeling companies, AIR and RMS, within a day of one another announced releases of new earthquake models for North America. The new model versions, based partly on the 2008 USGS National Seismic Hazard Maps, produce significantly reduced loss estimates for most regions of the U.S. While the amount of reduction varies by model, by region, and by type of business, most companies with significant earthquake exposure will see large reductions in their model loss estimates. Implemented as is, these changes will have major implications for company risk management decisions, including earthquake underwriting, pricing, and reinsurance purchasing.
The Executive Briefing answers the following questions in a format appropriate for senior executives:
What are the new models based on? How much faith can I put into the new models and how much confidence can I place in the new model loss estimates versus previous loss estimates? How can the changes in my loss estimates be tested? Are the model loss estimates likely to go back up, and if so, when? How should I use the models to get a more robust understanding of my company’s earthquake risk?
Any company that implements a new model without thoroughly testing and understanding what’s behind it is committing modeling malpractice,” said Karen Clark, President and CEO of Karen Clark & Company. “This Executive Briefing brings more transparency to the science underlying the new earthquake models, and helps companies enhance their risk management decisions by going beyond point estimates derived from models with such obvious and wide uncertainty."