Growing up in Beijing in China, just 50 miles south of the Great Wall, I always wanted to explore the US, another vast country, albeit one with a very different culture.
That's not to say that there are no similarities between the two nations, of course. In fact it's in my work as a Property underwriter where I see some things that are very familiar.
For example, both countries have a huge natural catastrophe protection gap – the difference between economic and insured losses. According to Swiss Re's 2015 Sigma Report, the US has the biggest protection gap of USD 30.9 billion, while China ranks third globally with a USD 22.7 billion protection gap.
Here you can find the recently published sigma report - Natural Catastrophes and Man-Made Disasters in 2016 for the most up to date information.
Yet despite sharing a large protection gap, there is at least one stark difference between the countries and that is the quality of the data available to underwriters who are trying to accurately price the risk of perils in the country.
Quite simply, data granularity in the US is more advanced. When I received my first submission from a US insurer, I was overwhelmed by the size of the data sets, especially the exposure data model (EDM) and result data model (RDM) files, which can provide precise details like latitude and longitude location data. In China, there are still clients recording the exposure data at province level. For example, an extreme case could be for Guangdong province, which is nearly 1.5x the size of California and 2x the size of France, but there is one exposure number used for nat cat modeling.
Pushing for more granular exposure data is vital to the accuracy of risk assessment. The reasons are:
1. From a modelling perspective, by inputting more granular data, insurers can benefit more from increased computing power and mapping abilities, thus getting more accurate results for their Nat Cat exposure, therefore more efficient risk management;
2. From an underwriting perspective, it's very important to understand the risk. For example a house located just two miles from the coast is much more exposed to storm surge and flood, compared to a house 20 miles from the coast. Data accuracy makes a big difference in our underwriting decision;
3. From a portfolio management perspective, by having more granular data (e.g. location, construction type, occupancy, etc.), companies can slice and dice their portfolio from different angles, identify trends and implement different strategies to improve the overall performance of the portfolio.
Advanced technology does and will continue to play a large role in improving data. We've already seen insurers in developing countries like China investing in technologies to improve their data quality in the same way the US market did previously.
Yet we must always strive for improvement and not rest on our laurels. By continuing to increase our understanding of perils and our ability to price the risks they pose, we will ultimately increase our resilience to them.
Category: Climate/natural disasters: Disaster risk, Resilience