The president and CEO of catastrophe-modeler Karen Clark & Co. explains why she’s convinced “Characteristic Event Analysis” offers a more effective method of cat-loss estimation and preparation than the insurance industry’s longtime focus on probable maximum losses.
In terms of what insurers need to be doing, what are the fundamental requirements for effective catastrophe-risk management?
After consulting with dozens of insurance and reinsurance companies over the past few years, we’ve found that insurers would very much like to have risk-management metrics with three fundamental qualities: consistency, transparency and operational ability. In order to effectively manage catastrophe risk, insurers need to fully understand the risk and how it’s being measured for their specific books of business. Insurers would also like a tool that enables them to monitor the effectiveness of their risk-management strategies over time.
What in your opinion is the greatest challenge P&C insurers face in predicting and preparing for hurricanes?
By focusing on probable maximum losses (PMLs) to manage risk, insurers frequently are surprised by actual events that cause losses over their PML estimates. The problem is that model-generated PMLs mask the major loss potential of 100-year events making landfall in specific locations. PMLs give a false sense of security, while Characteristic Event (CE) Analysis clearly shows where companies have exposure concentrations that will result in losses well above their 100-year PML loss estimates.
What differentiates the CE analysis approach from other methods?
The CE approach is transparent and is the right balance between fully probabilistic and deterministic approaches to catastrophe-loss estimation. CEs are defined-probability events created for the return periods of most interest to insurers—such as one-in-100 and one-in-250 years—and are floated across a book of property exposures to provide a complete analysis of the loss potential from representative-return-period events.
Because of the modeling process, PMLs are not operational and are highly volatile numbers. Instead of one number, CEs provide a range of loss estimates for the 100- and 250-year events that are stable, operational-risk metrics that can be drilled down to counties, ZIP codes and even individual policies for risk-management purposes. In this way, CEs provide valuable information—information that addresses the model limitations and complements the model-generated information.
Some media reports speculate that climate change is causing an increase in the severity and frequency of hurricanes. Do insurers believe this? How does this theory align with proven science?
There is no proven science with respect to climate change and hurricane frequency or severity, [but] according to the expert opinion of the U.N.’s Intergovernmental Panel on Climate Change, climate change is likely to decrease hurricane frequency and increase hurricane intensity over the next 20 years.
For insurers and claims professionals it takes just one major hurricane striking a populated area to create a very large industry loss—and companies should be prepared for this at all times. Historically, the worst loss given today’s property values would be a repeat of the 1926 Miami hurricane, which is projected to cause nearly $100 billion of insured loss if it occurs again.
—Interviewed by Christina Bramlet