Articles - Identifying the root causes of subsidence risk

Explaining the factors causing a ten-year spike in subsidence claims and how insurance providers can more accurately assess the growing risk through tree and soil data combined. Subsidence can be caused by man-made issues, like dramatic cases of mine shaft collapse, however the most common causes are natural, unseen and unpredictable which makes pricing for this risk a challenge for the insurance sector.

 By Richie Toomey, Sr. Manager, Commercial Insurance at LexisNexis Risk Solutions UK and Ireland

 Soils naturally shrink and swell to some extent with the effects of weather. Clay soils, in particular, are prone to shrinkage, while lighter soils can wash away from under foundations. However, trees can also be a significant root cause of subsidence. Vegetation absorbs water from the soil and can potentially cause shrinkage, but in the case of trees, the damage can be far-reaching. 

 Root spans of fully-grown trees can vary from eight metres for a pine to the imposing 40 metres diameter of a willow’s roots . The impact of the root system is, on average, as wide as the tree is tall. With these roots absorbing huge amounts of underground water, soil can be dried out under buildings to damaging levels.

 While insurance providers seek to understand the distance and height of trees in relation to the insured properties, last year’s subsidence event has spurred further investigation to gain a more precise understanding of the subsidence risk caused by trees. Could a database of 300 million trees - including their height, overlaid with soil and weather data provide the sector with the clarity it needs to underwrite this risk?

 Climate change and subsidence
 In December 2018, the ABI announced that following one of the UK’s hottest and driest summers on record , with 12 weeks of uninterrupted sun, subsidence claims had quadrupled reaching their highest level for more than a decade. In just three months, more than 10,000 households made subsidence-related claims, totalling £64 million and an average value of £6,400 per claim. In dramatic contrast, there were just 2,500 subsidence claims in the previous quarter, totalling £14 million. This increase of 350% is the highest quarter-on-quarter jump since records began more than 25 years ago.

 The figures for July, August and September 2018 show the highest level of subsidence claims since the record-breaking heatwaves of 2006 and 2003.

 Intergovernmental Panel on Climate Change (IPCC) predictions state that the average global temperature will increase by 1.5 degrees by 2030. Our changing climate will bring changing risks and subsidence years could become much more frequent.

 What a difference a tree makes
 Subsidence primarily causes damage to buildings when it occurs unevenly. If the ground under an entire building shrinks evenly, the building will simply sit slightly lower, as will its neighbours. It is possible to see in radar data from the Sentinel-1 satellite where large areas of landscape have sunk in dry conditions. The height difference of the ground between April and June 2018 reached a maximum of -0.134cm.

 However, especially during drought conditions, a thirsty tree may remove more moisture from the soil at one side of a building than the other, meaning that side of the property will subside quicker, resulting in structural damage.

 Assessing the risk at individual building level
 Data on the average or expected weather conditions, coupled with soil type, soil shrink and swell and likelihood of landslides already enable us to create a risk score which can be used in insurance pricing, providing an indication of a property’s propensity to subsidence.

 We believe that by adding to this mix key data for the 300 million trees across England and Wales will deliver a clearer picture of subsidence risk. The data includes tree height, which is used to highlight the area of potential impact, and any buildings in that at-risk zone.

 In testing, we have seen a dramatic increase in variation of risk in an area. Where once a whole village may be given the same risk score, or one street will be given a single score, with tree data added we can bring the risk prediction down to individual building level. We are then able to distinguish between high risk buildings and, for example, the buildings in high clay areas which are lower risk than the area average as they are not close to any trees. This is delivering more granularity and spatial-accuracy in the predictions and therefore allows for more accurate and fair pricing.

 With warmer summers set to become the norm in as little as a decade, subsidence surges are likely to become increasingly common. The good news is that data can be the insurance sector’s ally in helping to more accurately predict subsidence risk.
 Source: ABI subsidence stats, December 2018:
 Source: The Intergovernmental Panel on Climate Change (IPCC) 2018 Special Report: Global Warming of 1.5 ºC
 Source: Copernicus Sentinel data 2018

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