Reacting to an expert’s negative comments about insurance companies’ use of catastrophe models, industry representatives said carriers have improved their use and understanding of models since Hurricane Katrina.
Their comments came in response to a speech by Karen Clark, president of Karen Clark and Company and a pioneer in the modeling field. Ms. Clark said in a recent speech that insurers have become too reliant on catastrophe models when deciding which risks should be cancelled and which ones are acceptable.
She is not the only recent critic of catastrophe modeling use. A regulator this week suggested models had an excessive impact on rating firms and insurer rate requests.
Bob Detlefsen, vice president for public policy at the National Association of Mutual Insurance Companies (NAMIC), said he does not see an industrywide overuse of cat models, but he acknowledged that their use has become more prominent.
Mr. Detlefsen said that while some insurers may possibly be relying too heavily on them, “from what I hear, it’s a matter of how they weigh the results that the models produce relative to those more traditional underwriting factors.”
“It’s not that they’ve abandoned them in favor of models, but for some insurers the models are becoming more prominent in their calculations than was the case before Katrina,” he noted.
After Katrina, Mr. Detlefsen said, insurers may have drawn the conclusion that “relying on historical loss data is something that has to be supplemented by a technique like modeling that takes into account future trends.”
He noted that models help insurers account for prospective factors other than weather, including increased concentration of population along the coast.
Mr. Detlefsen said that models can tell an insurer how many people will be living in an area five or ten years from now, what structures may look like, etc. This information, he noted, can’t be captured relying on historical loss data.
Debra Ballen, executive vice president, public policy management for the American Insurance Association (AIA), pointed out that insurers also have a better understanding of how to use models than they did in the past.
She said decisions are not based solely on data reported by a model. “My understanding is that the actuarial standards of practice don’t allow a company to…pick up a model and pluck it into its ratemaking without [understanding] what the model is and also understanding what the appropriate risk is.”
Matthew Grant, chief markets officer at Risk Management Solutions (RMS), a modeling company, said that before 2005, communication between people using the models and senior management at insurance companies was worse than it is today.
He said senior management didn’t challenge those using the models to see where there may be gaps in the model results.
Today, he noted, “the quality of people using models continues to get better and better.” The users are sophisticated now, and more educated in how to use and apply model data. Senior management, too, is now asking the right questions, he added.
Mr. Detlefsen and Ms. Ballen also agreed that there is pressure from rating agencies and reinsurers to incorporate cat modeling into their underwriting.
At the recent Standard & Poor’s Insurance-Linked Securities Conference in New York, South Carolina Insurance Director Scott Richardson delivered a scathing attack on the way rating agencies use cat model results to pressure regulators into approving large rate hikes.
Mr. Richardson, using A.M. Best Co. rating agency as an example, said “they came into one of our companies” in South Carolina and said that if the company wanted to write in catastrophe areas, then it needed enough surplus to be able to withstand two 100-year storms and one additional catastrophe event to retain its ratings.
Noting that regulators had always looked at one 1-in-100-year event as the standard, he added, “I don’t have to explain to all of you that there’s a huge difference between two and one 1-in-100-year events.”
Both Ms. Ballen and Mr. Grant agreed with Ms. Clark’s comments about the importance of properly understanding models.
Ms. Ballen said there needs to be consistency with respect to exactly how models are used “so that there isn’t disconnect between, for example, a reinsurer’s evaluation of what the model means and the insurer’s evaluation, because that isn’t going to work.”
Mr. Grant said that models are sophisticated, and that it is important for users to understand what level of uncertainty there is in the results. The output, he said, is “not simply black and white,” and different levels of uncertainty exist depending on varying factors.