Access to data insights that offer insurance providers an accurate and comprehensive view of an individual’s motor insurance risk not only makes commercial sense but can create a better understanding of customer needs, helping to ensure the cover and premium is appropriate for the individual.
The use of industry contributed motor policy history data in the quote process is not a new idea. While No Claims Discount (NCD) entitlements have been shared since 2014, it is only recently that the critical mass of this data has been reached to allow for a greater understanding of how an individual’s car insurance policy history can help predict future losses – both in claims and cancellations.
Today, over 80% of the motor insurance market shares policy history data, creating a detailed record of key events such as cancellations, gaps in cover and MTAs, in motor insurance policies held by an individual over the past six years. Going beyond the operational savings and reduction in application fraud already offered by NCD data, policy history data can now be used to help determine pricing and underwriting strategies.
The true cost of customer behaviours
Recent analysis demonstrates the power of this data in helping the insurance market gain a fuller understanding of risk:
- There is a 50% higher loss cost when a customer has previously had a gap in cover
- An individual is 55% more likely to cancel if they have had one gap in cover in the past 5 years
- A history of past cancellations can equate to 70% higher loss cost
- A person with two prior cancellations is more than twice as likely to cancel again
- An individual with more than one NCD entitlement at any one time has a 33% higher loss cost
- Those who have had a NCD downgraded in the past are 60% more likely to cancel
- The more often people switch vehicles the more likely they are to cancel
The cancellation conundrum
Cancellations are a major cost to the motor market and counter-intuitive to insurance providers’ retention objectives. Based on our analysis, 15% of new business is cancelled across the motor sector and most of this business – 87% – is cancelled after the cooling off period, not before. This represents a significant cost in terms of fees, potential bad debt and loss of future custom. We estimate an insurer provider writing 100,000 new business policies a year could be losing in the region of £1.2m through cancellations.
Predicting the risk of cancellation has been very difficult up to now, but policy history data is providing a true understanding of cancellation relativity across the market. Looking at cancellation risk in relation to other risk factors allows insurance providers to do more than accept or decline customers. Quotes can be personalised – perhaps offering discounts to lower risk customers or potentially asking for up-front payment from higher risk applicants.
The power of data
Policy history data when used alongside other data sources such as quoting behaviour and public data, can create comprehensive customer risk profiles. Costs associated with cancellations and claims losses can be reduced, while loyalty is rewarded and promoted – all helping the market deliver more relevant products and fairer pricing to all of its customers.
Martyn Mathews, senior director, Personal Lines, UK and Ireland, Insurance, LexisNexis Risk Solutions