In the UK, re/insurers generally have property information that is geocoded to coordinate level. As the benefits of high-resolution hazard data infiltrate risk management practices, we're enabling catastrophe model analysis at building level, matching re/insurance portfolio exposure resolution to get the best flood loss estimates.
Using a uniquely detailed approach, JBA's updated UK Flood Model draws on our market-leading 5m UK Flood Map to assess risk at building level for river, surface water and coastal flooding.
Of the three flood types, surface water is particularly difficult to model because it tends to be channelled along roads and pools in natural depressions to form isolated pockets of flooding. As a result, the deepest water isn't always where the buildings are. Coarser modelling approaches often assess risk based on water that pools in natural depressions away from buildings, but by analysing flood at individual building level, only the hazard directly affecting the property is considered. As a result, we've seen variance in the estimation of average annual loss of as much as 25-30% for some UK residential portfolios by improving the resolution to building level.
The image below shows that floodwater can affect risk A, but only reach the front garden of the neighbouring building, risk B. The two therefore have very different annual average losses. Without the ability to differentiate the buildings from nearby roads, gardens and terrain to only analyse water depths affecting the building, risk B would have a much higher loss due to the depths in the garden being included.
Matching risks to buildings
But what if a risk is geocoded to the road and not precisely to the rooftop?
Instead of using the depth of water on the road, the model matches risks within 20m of a building to the nearest building for analysis. This method finds the balance between building level analysis and ensuring risks that are not perfectly geocoded are still correctly analysed.
Risk C in the image represents a risk geocoded to street address level. As the import location falls within the orange outlined area, the model associates it with the building for analysis and only the water depths affecting the building are used to estimate loss for risk C. The ability to identify risks that fall close to, but not directly on, the building, ensures portfolios without rooftop level geocoding are still making full use of the high-resolution hazard data and producing a robust estimate of flood loss.
Large and complex risks
But what about risks like industrial sites and caravan parks?
For risks that are larger and more complex, the model takes a different approach to ensure flood losses are estimated effectively. We explored this method in more depth in another blog post, flood modelling for large and complex risks.
And don't forget, not all coordinate data is created equal! To find out more about the difference in accuracy of geocoded locations, check out Ian Millinship's blog. For more information on our UK Flood Model, read our executive briefing.
