How insurance providers are making their customer data AI ready

Insurance providers across the globe hold billions of pieces of customer data within the four walls of their business – it is perhaps their most valuable asset. However, as generative AI and even more emerging technologies are being explored to allow insurance to become far more personalised to the individual, just how 'AI ready' is that customer data? 

The single customer view

'AI ready' means that any records for the same customer wherever they are held in the business, are linked so each department such as claims, quoting and marketing, has the same view of that individual. There are also no errors in those records such as changes of address, names being misspelt or out of date due to life events.  Plus of course each and every valuable customer record is properly utilised rather than left lying dormant, forgotten and out of date.

Ultimately, there should be one consolidated customer record for each individual that has ever had a relationship with business. This should offer a true representation of their history and dealings with the firm. Importantly, this record should include the customer data from any businesses that have been acquired in the history of the group.

Solving the customer data management conundrum

Attaining this one customer view, a view that automatically updates over time, might to many large insurance providers, seem unattainable without a huge amount of internal resource spent endeavouring to match and link their customer data. But this customer data management conundrum needs to be solved to enable the insurance market to maximise the advantages of AI.

The problem is that within the insurance market, merger and acquisition activity has been on the up meaning more customer data needs to be integrated and understood. There have also been high levels of shopping and switching.  This reached record levels in motor insurance in 2024 according to the LexisNexis® Risk Solutions Insurance Demand Meter U.K. due to a combination of the cost-of-living crisis and premium increases in the last few years.  

Every time an individual seeks a quote for insurance, asks for a mid-term adjustment to their policy such as adding an additional driver, lodges an insurance claim or is targeted with a marketing promotion, that creates a data point. Add to this the volume of policies typically held by an individual - 16 in the UK according the Financial Conduct Authority's (FCA) Financial Lives Survey. This means there are millions upon millions of interactions between insurance providers and their customers every day across the globe. The scale of data is huge but each touchpoint could be used as an opportunity to build a better understanding of the customer. 

AI to make insurance more personalised

So coming back to AI and more specifically generative AI to make insurance more personalised to the individual. Structured and accurate customer data is crucial. It empowers generative AI to respond with contextually accurate and customised information through chatbots and virtual assistants; it can be used to make more personalised policy recommendations; in claims, at First Notice of Loss (FNOL), AI can generate structured claims summaries from unstructured customer feedback, speeding up investigation and triage; and in marketing it can help generate targeted marketing copy, newsletters, or renewal letters.

A white paper by SAP Fioneer offers a further glimpse of what's to come such as proactive management of extreme weather events – from floods to wildfires. 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.'

One golden record for each customer

So where to start? Expert data science and data linking engines now enable disparate customer data held across an insurance provider and in multiple platforms to be matched with speed and accuracy.  It works by finding common threads across billions of customer records held across quotes, renewals, claims, marketing for all personal product lines, pulling on a large breadth of data including public and insurance policy history data to support that process. It then resolves multiple customer records down to a persistent identifier to create one 'golden record' for each customer, past and present, which updates over time.  The result is a 360degree view of each identity giving insurance providers the power to build the single customer view.

Clean customer data – the magic ingredient in generative AI

In such a competitive market, the customer data insurance businesses hold 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.

Yet customer data is key to delivering more personalised services 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. 

So the time is now for insurance providers to grasp the nettle and get their customer data 'AI ready', knowing that the possibilities of AI in insurance are exciting and potentially transformative. This is why some of the leading insurance brands in the world are now using data linking engines to remove much of the complexity of resolving customer data to make it clean, structured and ready to leverage for the good of the customer and the market.