RDT has been at the coal face of insurance technology for 27 years. We’ve created some of the UK’s most widely used insurance software and we’re committed to making insurance cheaper and simpler to sell and manage.
Applying for insurance has traditionally involved filling out a long form or spending an age on the phone with the insurer. But consumers are now coming to expect insurance to be sold like everything else is - whenever they want, wherever they are, and without any fuss or faff.
Very often a prospective insurance customer does not have the answers to all the questions being asked of them, meaning they have to guess, or worse, deliberately lie to get a better deal. This is where data enrichment and prefill combine to create a much-improved user experience and more efficient underwriting. With prefill, consumers provide only a small amount of information, such as name and address, and data enrichment takes over to automate the process.
A report on UK home insurance has underlined the benefits of data and analytics, and how technology providers can give insurers a competitive edge.
The report*, by LexisNexis Risk Solutions, is based on a study of digital trends among a cross-section of insurance professionals. It says that the use of big data has become the industry norm, with nearly all home insurers (89 per cent) now using data and analytics somewhere along the insurance chain.
However it found that only 57 per cent of them use data and analytics to price policies, while only 54 per cent use data to detect fraud.
A study by LexisNexis Risk Solutions has shown that home insurers could be working to improve the customer experience through better use of data.
Out of the 1,500 homeowners who were asked, 68 per cent believed that when applying for insurance it is acceptable to leave out or manipulate information to keep premiums low. Nearly two thirds (61 per cent) were worried that they might accidentally leave something out of their application, while 25 per cent said that claims should be covered even when the information originally provided was not entirely accurate.