By Sam Marsh, director of product management for UK and Ireland at LexisNexis Risk Solutions,
Within the insurance industry, the combination of quote, policy history and claims data forms what we see as a data trinity that can deliver crucial insights for insurance providers and enable them to make accurate and fair decisions. In essence the data trinity is the combined power of contributory databases - the more that is fed in from the market, the more the market as a whole benefits from enhanced insights on the individuals and assets being insured. And, as contributory data matures, the level of insight will evolve. But that’s not where the data stops, data enrichment for the individual, the asset and the location complements contributory data, building out the picture of risk further. This powerful combination of data is important because some data sets have a shelf life.
The Beast will vanish
For example, one of the most aggressive, recent weather fronts to sweep across the UK was the Beast from the East in 2018. In a rare event, this weather surge froze the entire nation. Icicles hung from Brighton Palace Peer while overnight lows dropped to -12C in some areas of Scotland . This nation-wide event created a 290% spike in bad weather insurance claims. Now that we are six years on from that frigid start to 2018, this historical, crucial data will be wiped from the industry databases.
This is why it is vital to ensure the industry shares its claims data going back much further than this. LexisNexis® Precision Claims, our cross market claims contributory database doubles this timeline to offer a 12-year history of weather-related claims for a specific property. This will support an accurate and fair assessment at quote and help ensure the customer is offered the right level of cover for their risks. We know if walls could talk they would have many stories to tell, so there’s no point in cutting the conversation short.
Looking at the market level
If we also look wider at a market level understanding of consumer behaviour around shopping activity, there are key trends insurance providers will want to consider when assessing risk and understanding the lifetime value of customers. For example, motor insurance quotation data gathered from across the market can reveal shopping activity. What we’re seeing is a significant increase in people shopping around. Comparing Q1 2022 to Q1 2023 there was a 18% increase in shopping activity based on LexisNexis Risk Solutions data. From Q1 2023 to Q1 2024, there was another 20% jump .
Motor insurance customers tend not to be loyal, and whilst quotation data shows us who is shopping, policy history data can reveal the extent of how many consumers switch providers.
In 2022, across the market, we saw a circa 16% rise in switching activity for motor insurance and there was a steady increase in 2023, taking levels to 22% . Understanding how an individual insurance provider’s experience of switching activity compares to the insurance market as a whole is interesting. Understanding how that individual insurance provider compares with their peer group is not just interesting, it’s very useful. There could of course be legitimate reasons for this as different insurance providers target different sectors and life stages and consumers can move through these a as their needs evolve.
These changes through the years make it even more important to combine quote and policy data to reveal how customers shop, switch, stay or even don’t shop at all. Combining this insight unlocks greater intelligence to make better decisions. Furthermore, cross searching claims behaviours across different product lines such as home and motor we can uncover further insights such as a whole pattern of activity that could help flag the risk of fraud before a policy is even incepted.
Ultimately, by combining industry contributed quote, policy and claims data and then complementing these insights with additional data on the property, vehicle and individual, we gain a fuller, more granular view of the customer and their asset. This blended approach not only limits the insurance provider’s exposure to risk that falls outside of their underwriting appetite but helps elevate the customer experience. By knowing more about the risk, insurance providers can do more to mitigate those risks and ensure the consumer benefits from the cover they need.
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