Author Archives: Paul Burgess

About Paul Burgess

Regional Vice President, Asia and Australasia

After performing climate modeling in academia, Paul joined RMS in 2000, during the early phases of flood modeling development, working on flood models for the U.K., Belgium and Germany, with a focus on the issues of off-floodplain losses.

Paul moved to a client facing role in 2005, working on the implementation and adoption of models within insurers, reinsurers and brokers. Since 2014, Paul has led the RMS presence across the Asia-Pacific region, based in Singapore.

China Reinsurance: Domestic or Global Expansion Both Require Risk Modeling

Paul Burgess, Client Director, Asia-Pacific, RMS

Erica Xue, Senior Product Manager – Model Development, RMS

In a country that according to the United Nations, between 1995 and 2015 experienced the largest number of natural disasters globally, and with these losses largely uninsured, China is at the start of a journey to close its protection gap between economic and insured losses — during a sustained period of rapid GDP growth. Examples such as the devastating Sichuan earthquake in 2008 which killed more than 80,000 people and caused US$125 billion in economic losses saw just 0.3 percent of losses covered by insurance. Floods in southern China during the summer of 2016 saw economic losses of US$20 billion, the second costliest event of the year. But again, according to Munich Re, just two per cent was insured.

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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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