This piece is by Sam Marsh, director of product management, UK and Ireland LexisNexis Risk Solutions, Insurance, which takes an in-depth look at the value of granular level data on claims.
Imagine these common claims scenarios – an individual bumps into the back of another car at traffic lights and claims on their insurance for minor damage. A week later, their friend next door has a more costly accident involving several vehicles on a roundabout – the claim is protracted, complicated and costly. They both see a rise in their premiums – the question is, how fair are those premium increases? Currently, an insurance provider would not know the liability at each stage of the claim, or detail on the loss cause and circumstances nor more detailed claims reserve and payment information when pricing the customer as a new risk. This lack of insight naturally hinders their ability to offer a fair and accurate quote. And, if a new claim arises once that customer is on board, it is difficult to put it into the context of any past claims.
A lack of highly granular claims data has been a weak spot for the market that is now being solved through the first cross-market claims contributory database – LexisNexis® Precision Claims. This is offering a detailed picture of the claims history for the person and the asset at point of quote through to claim. It means that the low-value traffic light collision can be considered in a very different way to the roundabout claim, for fairer new business quotes.
Now imagine this second scenario – an individual is moving into a new home and shopping for an insurance quote. They confirm the address and the insurance provider sees, through access to industry-contributed claims data, that the elevated premium is partly due to the property having had a series of claims for escape of water. The customer is shocked and annoyed. Not just because these facts were not revealed during the purchase process but because they consider themselves a good risk – in fact they have only had one low value home insurance claim in the past six years for accidental damage.
The insurance provider can see this is the case. They can also see just how severe the escape of water claims were and what was done to repair the damage. They decide to offer a discount on the policy in return for the property owner fixing an escape of water detector. This scenario is only possible through granular claims data on the person and the property at the point of quote, contributed by the market through LexisNexis® Precision Claims.
One final scenario bringing home and motor claims together at the point of quote, for the first time. An individual has not had the best insurance claims history. They’ve had two claims for car collisions in the past two years in their 2022 registered car, a windscreen claim and three claims on contents insurance for accidental damage to a TV, a lost watch and the theft of a laptop. One claim is still under investigation.
Shopping for motor insurance, they might be tempted to keep some of this history to themselves but decide against that. It’s a good decision as through LexisNexis Precision Claims, the motor insurance provider quoting for a new policy can see their full claims history across motor and home, including that windscreen claim and the status of the claim that’s still being investigated. This helps them price with a clearer understanding of the overall risk of the proposer. Additionally, the insight allows them to consider the cost of a future windscreen claim, knowing there is an increased chance of a windscreen claim occurring again.
It’s also a good decision because with this insight the insurance provider can consider the best product for the consumer’s needs given their chequered claims history. For example, they may want to offer comprehensive cover for personal possessions.
It all comes back to using data to know more, to do more for the customer. That means precise pricing but also taking steps to help mitigate future risks and hopefully reducing the claims losses that are pushing up the cost of insurance for all.
The ABI unveiled a series of steps the industry is taking to combat the rising costs of motor insurance cover, at its Annual Conference in February 2024. They pointed out that Ernst and Young estimate that for every £1 paid in premiums in 2023, £1.14 was incurred in claims and expenses. The cost of household insurance has also risen – up 13% in 2023 for building and contents combined.
Against a backdrop of increasing cost pressures and rising consumer expectations, the time is ripe for insurance providers to exploit the latest advances in data enrichment to help build trust and resilience against claims inflation. Cross-market contributory claims data through LexisNexis Precision Claims is set to change the customer journey – from quote to claim – for good.
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