By Helen Richardson, senior product manager, U.K. and Ireland, LexisNexis Risk Solutions, Insurance
Further explained, best practice equates to no unlinked records for the same customer, held in different departments of the business or different brands within the same group; there are no errors in those records such as misspellings or changes of address; there are no valuable customer records lying dormant, forgotten and out of date.
Instead, there is one consolidated customer record for each individual that is a true representation of every dealing they have had with the insurance brand and/or any brands within that group (including any which may have been acquired along the way). One customer view that is updated over time might seem like the Holy Grail of customer data management, but it is also absolutely essential that the insurance market get their customer data house in order to move at pace to maximise the advantages of AI, when they are ready.
The customer data insurance providers hold is perhaps their most valuable asset. It is what truly differentiates one insurance provider from another but the larger they are and longer they have been in the market, the more complex the challenge becomes of making sense of that data.
Consider M&A activity, increased levels of switching activity due to a combination of the cost-of-living crisis and premium increases in the last few years. Every interaction creates a data point and an opportunity to build a better understanding of the customer. But it also creates a vast amount of data that needs to be grappled with.
Consider also the volume of policies typically held by an individual – household contents; buildings; motor; travel; pet; health; dental; bicycle; breakdown; mobile phone to name a few. In fact, The FCA’s Financial Lives Survey in 2022 lists 16 individual personal insurance products bought by consumers each year. That’s not including any commercial insurances held. This choice is great, but it does present a big challenge when it comes to creating a comprehensive, 360-degree view of one individual based on all the touchpoints and relationships they may have now or in the past with an insurance business.
Why is surmounting this challenge important? First of all, the insurance market has a duty to put their customers’ needs first and provide fair value under the FCA's Consumer Duty. If they are not fully leveraging the customer data they already hold to understand their customer’s needs, they are going to struggle to meet their regulatory duties and obligations.
If we look at identifying vulnerability for example. Should one part of a business be alerted to vulnerability, that knowledge needs to be passed on to other areas of the business, with the customer’s authority. How can insurance providers make that happen if they can’t quickly identify that the individual has more than one relationship with their brand?
Utilising customer data to personalise how they support customers is now even more of a strategic imperative for the insurance market.
So this brings us back to AI and more specifically generative AI to make insurance more personalised to the individual. It has been estimated that if AI is utilised to its full extent, it could add over $1 trillion to the insurance industry annually . But insurance providers now need to work out how exactly they do this and where they should focus their efforts.
A white paper by SAP Fioneer examines the areas in which it could be used to enhance and transform the insurance proposition. This includes personalised insurance policies using automated policy drafting and scenario simulation; risk assessment and proactive management of weather events for example; individually tailored recommendations for customers and last but by no means least, claims processing. Personalisation has the potential to enhance the customer experience at each point of the journey, removing friction between the customer and the insurance provider and freeing up resource to focus on the areas in which human skills and empathy remain vital. As SAP Fioneer states, ‘Consumers will soon come to expect this level of personalisation as standard. So it is vital for insurers to be able to meet and exceed that expectation.’
So where to start? It goes without saying that insurance providers have a huge amount of data expertise, but it is extremely difficult to match customer records held in different parts of a business – especially if an address or name or even a date of birth might have changed through an input error.
However, expert data science and advanced linking algorithms now enable disparate customer data held across an insurance provider and in multiple platforms to be matched with speed and accuracy. Advances in customer identity resolution means common threads can be found across billions of customer records held across quotes, renewals, claims, marketing for all personal product lines. The success of this approach comes down to the range and quality of data used to match and link the customer data. That’s where outside help can be so valuable.
The match rate of the customer identity resolution solution - LexID® for Insurance - is high because we have made considerable investment in a wide range of datasets. It pulls on a large breadth of data including public and insurance policy history data to resolve multiple customer records down to a persistent identifier (LexID number).
The result is one ‘golden record’ for each customer, past and present, which updates over time. With a 360degree view of each identity, insurance providers have the power to build the single customer view to create attributes to support underwriting and pricing as well as in fraud detection, compliance (such as data subject access requests) and claims.
The possibilities of AI in insurance are exciting and potentially transformative. 2025 should be the year insurance providers get their customer data AI ready utilising innovations in linking and matching technology to make this complex process simple.
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