Insurance derived data is gold to brokers

Authored by Martyn Mathews, senior director of personal and commercial lines, LexisNexis Risk Solutions, Insurance.

It’s a little-known fact that around one in ten motor insurance policyholders is underestimating their current No Claims Bonus (NCD) discount. In contrast and perhaps of more concern is the fact that 13% of motorists are actually over-estimating their NCD.

Forget paper proof, the digitisation of NCD proof through an industry wide contributory database, is a great example of how data enrichment using insurance specific data, is helping Brokers identify exactly which individuals are over or under reporting NCD, to help ensure the right risks are being delivered to insurance partners. But NCD is just the tip of the iceberg. Every day, for the past 6 years insurance providers have shared policy history and quote data so that they can access a market wide view of a customer at quote.

The value of insurance derived data to the broking community cannot be over-exaggerated. How else could brokers know with any certainty the risk of cancellation based on the industry’s past experience with that customer, or whether they have had a gap in cover in the past few years?

Drivers in the UK cancel around 1.3 million car insurance policies each year and are a particular challenge for the broker community, who by the time the policyholder has decided to cancel their policy have incurred substantial marketing and admin costs.

In addition, from a pricing and underwriting standpoint, historically cancellations have a direct correlation with insurance claims and are therefore a powerful attribute to help calculate pricing. People without a mid-term cancellation have on average a 7% lower loss costs (claims frequency and claim severity) when compared to the whole market. In contrast, people who on average have more than one mid-term cancellation through to 6+ mid-term cancellations, have between 35 percent to 230 percent higher loss costs relativity when compared to the market.

But what about cancellations or gaps in cover as a consequence of lockdown? Context is everything when assessing risk so knowing through policy history data that an individual chose to cancel a policy in the first, second or third national pandemic lockdown throws an entirely different light on the risk.

Insurance shopping and quoting behaviour can also offer brokers powerful insights – they can indicate named driver risks and fronting; the risk of a claim based on the timing of quotes across a 90 day window and the risk of quote manipulation to gain a lower insurance premium.

Clearly having this type of data enrichment at their fingertips would enable brokers to assess risk far more accurately to lower operational costs, increase quotable business opportunities, lessen fraud and improve pricing accuracy.

Yet 56% of brokers we recently surveyed in a joint webinar with Open GI currently use zero or one third party data source to help them deliver the volume and breadth of risk their insurance partners want.

With 35% of brokers citing non-return of documentation and 23% saying on-boarding and processing costs have the biggest impact on their business; it is clear that adopting digital data technology to assist in these areas would really positively impact the majority of brokers.

On the commercial side, 67% of brokers said their panel of insurers are asking for enhanced ‘know your customer’ validation checks, the ability for brokers to verify that prospective small business customers are who they say they are will not only improve their insurer relationship, but also allow brokers to widen their footprint and quote for more business.