Tag Archives: canterbury earthquake sequence

New Zealand Earthquake Risk: It’s All in the Details

Across the global risk management community, we are bombarded by new information every day. As risk professionals we have to prioritize how we give our attention to new information. From an RMS perspective, when we release new model insights, we know there is a need to be concise and boil down huge research projects into just the important details. But there is a concern that the top-level results get taken as a uniform value that can be applied across the board, losing vital nuance.

When RMS released its New Zealand Earthquake High-Definition (HD) model in mid-2016, an important message was that the annual average loss (AAL) had increased by 30 percent. The ground-up, all-lines, countrywide AAL increased 30 percent relative to the previous version of the model released in 2007. An increase in loss came as no surprise after the Canterbury Earthquake Sequence of 2010/11 – see our New Zealand earthquake blogs.

The HD model was launched at two industry seminars in Wellington and Auckland and came with online documentation: some 44 pages of Understanding Changes in Results and 114 pages of model methodology, supplementary materials on our RMS OWL client portal and a team of modelers happy to talk about their work.

Faced with this information, one approach is to note that the New Zealand market is very consolidated so industry figures should be useful guides for actual portfolios. Let’s just use the old model and scale it by 30 percent. “She’ll be right”, as they like to say in New Zealand. But with two models being so different, this scaling-up would not make sense. Why are they so different?

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Starting the Trend Toward More Differentiated Risk Selection and Pricing

There has always been a balance between cross-subsidy and property-specific, risk-based underwriting and pricing in insurance, particularly for homeowners’ policies. While an actuary can easily quantify differences in fire risk for houses constructed from wood versus concrete based on claims, this becomes much more difficult when the peril concerned is infrequent, such as for earthquake or flood. Clearly risk models help to bridge this gap, but facilitating a move from cross-subsidy to risk-based pricing is more complex than simply using risk analytics. Factors such as regulation, market conditions, distribution channels and insurer IT systems all determine whether individual insurers and markets will move towards greater differentiation of risk. This is not to mention the political dimension of insurance affordability and social equity.

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