HOME INSURANCE PROVIDERS GAIN NEW POWERS TO HELP OFFER FAIRER PRICING THROUGH LEXISNEXIS® PROPERTY INSIGHTS

New Relationship with Outra Puts Industry-leading, Comprehensive Property Data at Point of Quote

 

From rebuild cost to square footage and listed-building status to roof type, home insurance providers can now assess risk based on insights from an extensive set of data about a property down to its individual characteristics, going beyond the information traditionally used or requested in the quote process.  LexisNexis® Property Insights is one of the first property data enrichment solutions to combine multiple predictive attributes for an individual address from the choice of 27 property characteristics from Outra, the predictive data science business.

This combined data is set to support the market as it adjusts to new pricing rulesi, allowing insurance providers to build a very detailed picture of risk for new business and renewal pricing, and to help ensure products are suited to the customers’ needs. It also reduces the reliance on customers to fill gaps in knowledge about their properties.

The data available from Property Insights can be injected at the point of quote through the LexisNexis® Informed Quotes platform, which connects to all major software houses. This offers a single point of access to a highly comprehensive range of datasets to help inform quoting and underwriting decisions, allowing insurance providers to speed up the quoting process and reduce referrals. The data can also be used to pre-populate application forms, for example, rebuild cost and year built, saving consumers time while helping to ensure accurate and competitive quotations.

Consumer research by LexisNexis® Risk Solutionsii has found that while 57% of homeowners shop every time their policy is up for renewal, 11% rarely shop, simply renewing each year with the same provider. Accessing a much wider set of data during the quotation process can help insurance providers utilise fair and effective pricing strategies for both existing and new customers in accordance with the new pricing regulations.

Neill Slane, senior vertical market manager, U.K. and Ireland at LexisNexis Risk Solutions, commented: “Access to a detailed, 360-degree view of risk through Informed Quotes can give insurance providers the power to deliver on competitive pricing and good customer service expectations and help demonstrate to the FCA the steps they are taking to build the most informed view of the risk. Thanks to our new agreement with Outra, insurance providers can use Property Insights for granular data on property characteristics, in addition to other datasets already in use like perils, to gain a deeper understanding of the risk.

“The availability of this level of detailed, verified data can help insurance providers differentiate their offerings to customer segments and deliver more personalised quotes. In addition, improved risk assessment of the property helps to speed up the quote process for homeowners, improve loss ratios and profitably grow portfolios. This can be hugely beneficial in a competitive market where insurance providers cannot take loyalty for granted and where pricing is coming under much greater regulatory scrutiny.”

Giles Mackay, CEO of Outra adds: “This new agreement with LexisNexis Risk Solutions will help insurance providers leverage the power of our comprehensive set of property characteristics data for the first time through Informed Quotes.  We are delighted that through this new relationship we can provide the data that helps to power Property Insights – a timely new solution for the home insurance market.”

LexisNexis® Property Insights comprises extensive and highly granular property data characteristics from Outra about the property.  There are 27 different data attributes including number of bedrooms; bathrooms; kitchens; reception rooms; when the property was built; floor area; heating type; roof type; listed status; rebuild cost; sale value; rental value; tenure; last sale date; last rental date and parking availability.

 

spot_img

Explore more