APIs – the secret weapon to underwrite disaster risk more efficiently and accurately?

Droughts and wildfires in Europe and California, floods in India, typhoons in Japan and the Philippines – last year’s devastating disaster events highlight a global phenomenon: The costs of natural catastrophes are rising, and most of them are not covered by insurance.

This means that communities face a large and widening protection gap, especially in the world's densely populated urban centres. According to the Swiss Re Institute, the global natcat protection gap amounted to a staggering USD 219 billion in the two years 2017 and 2018.

One of the main reasons why underinsurance is so widespread is that too many people and businesses simply aren't aware of the risk they face or of the insurance options available to them. Equally, many insurers are reluctant to offer coverage where risk assessment is uncertain. So how can we tackle this dual challenge and help narrow the protection gap?

Raising awareness, improving assessments

An essential step is to increase risk awareness. Another priority is to integrate more accurate risk assessments in our underwriting. At Swiss Re, we use our geo tool CatNet® to address both of these concerns. We share it with our insurance clients so that they, in turn, can make their customers more aware of risks in their home location and confidently underwrite more business using the latest risk models anywhere on the globe.

Typically, a first meaningful measure is to get an overview of the hazards associated with each peril across all relevant locations. Hazard maps are a well-known and convenient tool to do just that – and nowadays they are usually provided with a browser tool. Swiss Re's CatNet ® is one of them, and it's been used by our clients for over a decade now.

But while it's practical to use the data in a browser-based tool, it is often not the most efficient way to facilitate an underwriter's daily work. Instead, so-called application programming interfaces (APIs) offer a much higher degree of automatization and more immediate operational support because they can feed data, maps, model results etc. right into an insurer’s own underwriting tools.

APIs at work

Suppose we want to underwrite risks with special care if they are in a 100 year flood, 500 year tsunami or 500 year storm surge zone. This is a perfect example of where a fully automated process using an API could greatly enhance the efficiency of the underwriting process. Instead of opening a browser tool, searching for the location and finding the right map, it is often more convenient to add a small component to your in-house underwriting system which provides all three pieces of flood data instantly.

For this reason, we upgraded CatNet® to include API functionalities just a few years ago. They can be called from most tools, even a standard spread sheet. The tool sends the latitude/longitude of a given location and the requested peril information to the CatNet® API to obtain an instantaneous hazard attribute back, for example a flood zone indication. This also works for many different locations at the same time.

More and more of our clients are starting to use our API services to become more efficient and more accurate in their underwriting. What is covered in the service is the same data as in CatNet® itself, and sample data sets of 10 natural perils are available here.

Underwriting experience matters

But does all this replace the underwriter? The answer is a resounding "no." Although automatic processes can greatly enhance efficiency and accuracy, they cannot replace the experience and judgment of a seasoned underwriter. Caution is still always required. This is especially true for irregular local data sets related to flood, landslide, subsidence and other zones6 where latitude-longitude searches can generate random results.

A human interface is still recommended to assess expensive locations. When interpreting a flood map, it’s important to also consider things like the topography of a location, its built up areas, the position of a river channel, the protection measures and any gradients. So, are geo APIs really a secret weapon in making underwriting more efficient and accurate?

Retrieving data from expert sources via APIs is indeed a useful ‘door opener’ for underwriting risks in non-modelled areas. But a thorough check by an experienced underwriter is still recommended for cases involving higher risks, such as the unexpected damage caused by last year’s extreme weather events.

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