Jonathan Guard, Director, Commercial Markets, LexisNexis Risk Solutions, UK and Ireland looks at how insurance providers can utilise the latest data and technology for protection and prevention ahead of what could be the coldest January and February the UK has experienced in decades.
In 2018 the infamous ‘Beast from the East’ cost UK insurance providers over £300 million in claimsi. Now scientists are warning that the first two months of 2020 could see temperatures dip even lower, pushing the potential cost of claims higher still.
With extreme weather set to become more commonly attributed tied to climate changes, insurance providers are calling on more data to help reduce their exposure to risk and improve their resilience to weather related losses.
Improvements in the accuracy of weather predictions are already allowing preventative action to be taken ahead of severe weather events, reducing the eventual cost of claims. In addition, the depth and breadth of data for the property, the policyholder and the location combined with data visualisation tools are evolving to give insurance providers a clearer picture of risk. This is not only valuable for pricing but for working out accumulations across a book of business and exposures as events unfold.
What a difference data makes
The ability to predict flooding for example has improved through access to detailed flood information going right back to the time just after the end of WWII – 1946. Adding this historical information brings a greater level of accuracy to assessing flood risk which goes right down to the individual property. We can even determine the different risks at the front of the property versus the back.
We must also credit LiDAR technology for the depth of knowledge we now have around environmental risks. Using the pulse from a laser to collect measurements, LiDAR enables 3D models and maps of terrain, showing buildings, trees and water levels for the whole of the UK. The insights provided are particularly valuable in flood modelling, as the data can be coupled with soil type, average rainfall and river gauge monitoring and used to accurately predict where water will go in a flood. It can also be used to show effectiveness and any potential consequences of manmade flood defences.
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 subsidence/heave risk score which can be used in insurance pricing. The next step is adding data on the location and height of the 300 million trees across England and Wales. This can not only help bring greater accuracy to subsidence and heave risk, but can be used to understand the potential impact of tree damage in storms, highlighting the area of potential impact, and any buildings in that ‘at-risk’ zone.
Using data on trees, the risks of soil swelling or contraction is much easier to determine, bringing the risk prediction down to individual building level.
Now that we have such a fine degree of understanding of environmental risk, the next natural step is to bring in historic claims data through a contributory database of property claims. This can enable insurance providers to consider outcomes for past claims relating to both the individual and the property, whether or not they have had a policy with the insurance provider in the past.
This enables more accurate risk assessment and pricing, and also highlights how best to support their customers both prior to and following an extreme weather event.
With extreme weather conditions becoming more and more common – with snow storms in February or heatwaves in July – the insurance industry must continue to adapt and utilise the latest tech and data. Only in this way can they ensure they will always have the best possible understanding of potential losses and the opportunities that exist to help customers prepare for extreme weather events.