Caroline Elliott-Grey, senior product manager, U.K. and Ireland, for LexisNexis Risk Solutions, Insurance, takes a look at the value of geospatial data.
Empowering brokers with swift, cost-effective access to perils data at the point of quote is becoming increasingly important. University of Bristol research reveals that annual damage caused by flooding could increase by more than a fifth in today’s terms over the next century. That could be reduced if pledges to reduce global carbon emissions are met. Nevertheless, insurance customers are already feeling the pinch. In the 12 months up to January, home insurance customers claiming for water-related damage saw quoted price rises of 49.1%. As price rises prompt consumers to reappraise their finances and perhaps consider switching providers, brokers can now up their game using geospatial intelligence data to help mitigate risk, personalise quotes and even cross-sell other products.
Shifting climate encourages brokers to up their data game
The UK climate is already moving towards drier summers, with wetter, warmer winters. Indeed, this year witnessed the south of England experiencing its wettest February since Met Office figures began. This points towards the urgent need for better planning, increased flood resilience in buildings and the use of appropriate geospatial data to mitigate risk.
Larger insurance providers have been using geospatial intelligence data directly injected into their workflows for some time now. Historically though, smaller brokers have struggled to access the wide-ranging perils data needed to obtain the essential facts about perils risk and the characteristics of the properties they are seeking to quote. More recently, however, these insights have become accessible to smaller brokers through a new broker-specific data enrichment solution, LexisNexis Geospatial Risks – a streamlined and cost-effective package of perils and property data for use at the point of quote, mid-term adjustment and renewal.
By combining perils risk scores for flood, subsidence and crime for the customer’s address, plus the property characteristics for their home (such as the roof type, number of bedrooms, construction type), a swifter and more accurate assessment of risk is achievable. This not only helps in providing a frictionless quoting experience for the customer but puts brokers in a better position to offer the most suitable product for the customer’s needs while ensuring the risk meets the appetite of their insurer partners. This reduces the potential for referrals or adjustments post-policy inception and the unnecessary friction that can cause with customers, aside from the additional admin this creates for the broker.
The predictive nature of the data also means brokers could also help customers consider how they could limit future risks such as spotting signs of subsidence early or thinking about enhanced security if their home is an area of high crime risk.
Tapping into new prospects
The additional advantage of geospatial data is how it may also help identify cross-sell opportunities. If a broker knows up front that a home with a garage is at flood risk, they may want to discuss protection for the customer’s car or motorcycle stored there. As climate change continues to alter home insurance risk, brokers can’t afford to stand still in an increasingly data-driven world.
Growing competition and changing customer behaviours are driving the need for data enrichment in the broker market. The more that is known about the property and its location, the more opportunity brokers will have to offer products suited to their customer’s needs. With consumers at the hard end of price rises, brokers who can approach them with a more personalised home insurance premium offering cover for known risks specific to their address, should get a warm welcome.
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