Home claims data can build a clearer picture of risk

In a Covid-19 world, market-wide claims data could be an ally for home insurance providers and their claims teams, writes Neill Slane of LexisNexis Risk Solutions

There is little doubt that the home insurance market is preparing itself for a change in risk profiles created by the Covid-19 pandemic. Accidental damage claims are expected to increase (think of all those pandemic purchased puppies and Joe Wicks classes), while, conversely, burglary claims may fall. The latest research from Consumer Intelligence shows that the average buildings and contents policy has fallen by 0.3% in the last three months. Even so, some homeowners are considering cancelling home contents cover because they feel at less risk of burglary, while others plan to cut back on essential cover to save costs.  

Front of mind for the market will also be the risk of extreme weather events following the storms and floods at the start of the year, which resulted in £360 million in claims payments. Supporting customers with fair pricing at quote and with exceptional levels of customer service during the claims process, while reducing exposure to claims fraud, is a tricky balance to achieve at the best of times, but in a Covid-19 world, the challenge has intensified.

Doing the right thing for customers, treating them fairly based on their individual risk—not the risk of their next door neighbour, or the general risk of their postcode—comes down to having the right data at your fingertips to create the most holistic view at point of quote, underwriting and claim.

Perils data is already widely used by the market, but it’s only this year that it’s been possible to access this data at the point of quote alongside 42 further data enrichment sources to achieve that immediate view of risk. This has been a big step change in automating and speeding up the quotation process. For the claims professional this is also good news, as this data could be utilised at point of claim to help inform claims treatment strategies.

Adding a completely fresh dimension to this picture is the addition of claims history data contributed by the market—early contributors to this database are already on board. Access to a market-wide pool of claims history data will bring a much greater level of understanding on the nature of prior claims—the circumstances, the settlement, the parties involved and much more. This will provide the opportunity to do a deeper dive into the data to understand more about claims losses in household and the predictive factors for those losses.