Foreign Adapted or Local?

Two weeks ago, I had the pleasure of speaking at the Australia’s first catastrophe risk management and modeling conference, which brought together all Australian modeling firms, brokers, and insurance companies in one place.

As in other insurance markets around the world, new regulatory directives are bringing increased focus on in-house understanding and ownership of risk, and in Australia specifically driving at board-level understanding of catastrophe model strengths, weaknesses, and associated uncertainties.

As I commented in a previous post, the ability to embrace model uncertainty and make decisions with awareness of that uncertainty is helping build a more resilient insurance and global reinsurance market, able to survive episodes like the record losses posted in 2011.

A.M. Best considers “catastrophic loss, both natural and man-made, to be the No. 1 threat to the financial strength and policyholder security of property and casualty insurers because of the significant, rapid, and unexpected impact that can occur. And simultaneously that the insurance industry overall has been trending toward a higher risk profile.”

They believe “that ERM—establishing a risk-aware culture; using sophisticated tools to identify and manage, as well as measure risk; and capturing risk correlations—is an increasingly important component of an insurer’s risk management framework.”

Catastrophe models, used appropriately, will continue to grow in importance as the only tool realistically able to help insurers and reinsurers understand their possible exposure to future catastrophic events. But we must always remember that models are the starting point, not the end point.

A topic of debate at the Australasian catastrophe risk management conference was whether “foreign adapted” models can be relied upon as much as “local” models to represent the risk accurately. The truth everywhere is that global catastrophe experience is much greater than local catastrophe experience in any particular country, and this is the case for Australia, particularly if we look at earthquakes or tropical cyclones.

The ideal model is one that blends that global experience and learning and adapts it where relevant to local conditions, working with local scientists and engineers to ensure that its accurately tuned to the physical and built environment.

We recognize that different perspectives exist, and that each insurance and reinsurance company needs to take direct ownership of understanding the different views of the risk that are available, and deciding which is most appropriate to use for their business. The ability for modeling firms such as Risk Frontiers to make their suite of Australian catastrophe risk models available on RMS(one), as announced at Exceedance 2013 will facilitate the ability for insurance and reinsurance companies to achieve this goal.

With the world’s population continuing its inexorable rise, and with more and more people and industries situated in hazardous places around the globe, the insurance industry can only expect its risk exposure to continue to increase.

Increasing the global availability of multiple model views will give rise ultimately to both a bigger community of model developers, and a more informed industry, with in-house expertise in catastrophe models and risk to support this global population and economic growth.

SVP, Business Solutions, RMS
Claire leads the models & analytics solutions group at RMS, responsible for guiding the industry’s understanding and usage of catastrophe models, identifying market trends and future needs, and informing RMS’ model development and communication strategies. In this capacity, Claire and her global team interact frequently with clients, regulators, and rating agencies to educate and advise on topics such as model roadmap, uncertainty, and appropriate usage. She is a member of multiple industry task forces and advisory boards, and frequently speaks at industry events. Prior to joining RMS in 2000, Claire completed 3 years post-doctoral research. Claire holds a BSc in environmental biology and a PhD in surface water modeling from Cranfield University in the UK.

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