LONDON and ATLANTA – LexisNexis® Risk Solutions, a leading provider of data, analytics and technology, has added Flood Re data to its data platform for home insurers and insurance brokers. The addition enables insurers to automatically identify any property that qualifies for Flood Re1 at the point-of-quote and understand the cost of ceding to the program. Together with building-specific flood modeling data already provided by LexisNexis Risk Solutions, insurers can make better decisions regarding the price to quote and whether to cede the policy to Flood Re. The solution is being used by several leading insurers and is available for both direct insurance business and broking channels.
When winter storms Desmond, Eva and Frank hit recently, the combined insured losses in the UK were £1.24bn2. These losses, the information requirements of Flood Re and concern that UK expected annual damages from flooding may rise drives the need for home insurers to gain a better insight into their household risks through building-specific information and exposure management.
The LexisNexis Risk Solutions data platform provides building-level flood data which is critical for managing Flood Re and allows home insurers to automatically flag those risks which may be appropriate to cede to Flood Re. The platform also provides the opportunity for insurers to easily add new data sources through the same connection and to continually enhance their home underwriting processes in the future.
“As insurers look to enter the programme and onboard as fast as possible, we are very pleased to be working closely with LexisNexis Risk Solutions as they facilitate getting their clients up and running," said Andrew Creedon, Insurer Engagement Director, Flood Re.
“This new solution underscores the commitment of LexisNexis Risk Solutions to continuously bring new and meaningful data and analytics solutions to market enabling our customers to make better decisions throughout the insurance workflow and improve their profitability,” said Bill McCarthy, Managing Director, LexisNexis Risk Solutions, UK and Ireland. “We recognise the importance of Flood Re in ensuring all home owners continue to have access to affordable flood insurance. With building-level flood data and key Flood Re data at the point-of-quote, insurers can more accurately assess and price flood risk – to enhance and enrich their household underwriting process.”
Through the LexisNexis Risk Solutions insurance data and analytics platform built on HPCC Systems™, home and motor insurers are able to leverage new data sources and data enrichment – all through a single point of entry – allowing them to continually improve risk selection, pricing and enhance long term profitability. The platform provides personal lines insurers with a greater understanding about the asset itself, its location, the insured’s risk profile and previous claims history.
LexisNexis® Risk Solutions harnesses the power of data, sophisticated analytics platforms and technology solutions to provide insights that help businesses across multiple industries and governmental entities reduce risk and improve decisions to benefit people around the globe. Headquartered in metro Atlanta, Georgia, we have offices throughout the world and are part of RELX (LSE: REL/NYSE: RELX), a global provider of information-based analytics and decision tools for professional and business customers. For more information, please visit LexisNexis Risk Solutions and RELX.
1The Flood Re scheme is designed to help the UK insurance industry to offer lower cost flood insurance by providing a re-insurance scheme for the entire industry. When a policy is passed into Flood Re, the insurer will be charged a fixed sum dependent on that property’s council tax band. For higher risk homes, this set price will be artificially lower than the price in the market which is based on risk, meaning the insurer should be able to offer the customer a lower price for the flood part of their insurance. https://www.abi.org.uk/Insurance-and-savings/Topics-and-issues/Flood-Re/Flood-Re-explained
2 Source: PERILS available at https://www.perils.org/web/news.html