Why use Subsidence Risk?
Traditionally, the risk of subsidence is associated simply with geology, geography, and any likely ground disturbance. The enduring question is, can we predict the risk of subsidence more accurately at a granular level, to good effect, across a geographically disparate book? And is the margin worth it if that process involves complex, ever-changing data? We believe the answers are 'yes', and 'always'.
Property by property, it's been established that the proximity of a single tree's root system may be just as much of a culprit as a nearby coal-mine. The height and breadth of canopies can also play a part in setting levels of risk. The trouble is, that tree data is complex and analysts need it to be interpreted at address level to make it useful.
However, Subsidence Risk enables insurers to examine a rated combination of the many factors that act as catalysts for subsidence at that individual, case-by-case level.
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