This piece is by Helen Richardson, senior product manager, U.K. and Ireland, LexisNexis Risk Solutions, Insurance
The insurance market is being revolutionised by generative AI and other emerging technologies that promise to make insurance more personalised to individual needs. However, to truly maximise the opportunities AI offers, an insurance provider’s customer data must be AI-ready.
That means one consolidated record for each customer that serves as a true representation of every dealing they have had with the insurance brand(s) within that group. Imagine, no more unlinked records for the same customer, held in different departments of the business or different brands within the same group; no errors in those records; no valuable customer records lying dormant. The ‘Holy Grail’ of customer data management? Maybe, but essential to capitalise on AI.
Customer data is a major asset for any insurance provider – it is what truly differentiates one brand from another. But the larger they are and longer they have been in the market, the bigger the challenge becomes of making sense of customer data across their books of business.
Mergers and acquisitions as well as switching and shopping activity have created more interactions and transactions, providing an opportunity to better understand a customer, but also creating much more data to be managed.
Add to this the volume of policies held by an individual – 16 according to The FCA’s Financial Lives Survey in 2022, not including commercial insurances. This all adds to the challenge of creating a 360-degree view of a customer. Imagine how much more insurance providers could do for their customers in pricing, product selection and claims knowing at all points of the customer journey every past interaction they have had with that individual across all lines of business.
This is aside from the fact that the insurance market has a duty to put their customers’ needs first and provide fair value under the FCA’s Consumer Duty. A more comprehensive view of customer data to understand their customers’ needs will therefore also help them to meet their regulatory duties and obligations.
So, where to begin? Expert data science and advanced linking algorithms now enable disparate customer data held across an insurance provider in multiple platforms to be matched quickly and accurately. Advances in customer identity resolution means common threads can be found across billions of customer records held by varying departments within an insurer and the product lines on which it focuses. The success of this approach depends on the range and quality of data used to match and link the customer data.
As an example, the match rate of LexID® for Insurance – a customer identity resolution solution from LexisNexis® Risk Solutions – Is very high due to significant investment in a wide range of datasets. Drawing on a multitude of data, including public and proprietary data, it boils multiple customer records down to one unique identifier (a LexID number).
The result? A ‘golden record’ for each customer, past and present, which updates over time giving insurance providers the power to build a single customer view and create attributes to support underwriting, pricing, fraud detection, compliance and claims.
A white paper by SAP Fioneerii examines the areas AI could be used to enhance and transform the insurance proposition at each point of the customer journey. This includes personalised insurance policies using automated policy drafting; individually tailored recommendations; and claims processing. The potential of AI in insurance is exciting. That’s why insurance providers should focus on making their customer data AI-ready now, leveraging advances in linking and matching technology to streamline this complex process.
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