Carla McDonald, director of product management, LexisNexis Risk Solutions, UK&I
Additionally, this data is often in siloed lines of business and simply used to confirm a previous claim declaration. That can leave gaps in knowledge not just for pricing accurately and fairly, this siloed approach makes it difficult to identify potential fraudsters claiming on multiple policies across multiple lines of business. Those gaps also make it difficult to assess a new motor or home claim in the context of a customer’s broader claims history, unless they have remained with the same insurer over time.
Cross market claims data offers greater context
Cross market claims data offers a solution both at underwriting and claims stages. It enables insurance providers to better predict claims losses based on an individual’s claims history and help expediate claims with a fuller picture of the market’s claims experience with the policyholder.
In the same way the vast majority of the insurance market now shares policy history data to help automate No Claims Discounts and gain predictive insights on cancellations and gaps in policy, it’s taken market collaboration to create the first cross-market contributory claims database combining home and motor claims history with cross-search functionality.
This delivers a granular view of home and motor claims history for an individual and the asset at the point of quote, mid-term adjustment, renewal and claim to participating UK insurance providers. This is one way in which claims intelligence is reshaping risk assessment and claims handling.
Delivering underwriting data to the claims end
Turning to the claims process, insurance providers need better data to settle claims quickly, control costs, prevent fraud and keep customers satisfied. While pricing and underwriting have become increasingly data-sophisticated, claims handling often still relies on fragmented, reactive processes.
In motor specifically, claims volumes remain high, vehicle complexity is accelerating, fraud is becoming more sophisticated, and customers increasingly expect the same speed and transparency they get from online banking or retail. Yet many insurance providers and claims management firms are still trying to manage claims decisions with incomplete, inconsistent and disconnected data.
Claims decisions are only as good as the data at FNOL
At FNOL, insurance providers are often forced to make early decisions based on partial or inaccurate information. Critical details about the vehicle, the policyholder, third parties, coverage and risk context are often missing or incorrect.
That creates immediate downstream problems. It means that claims teams waste valuable time simply validating basic facts, claims can end up misrouted to the wrong garage for the work, cycle times get longer and costs escalate unnecessarily.
In a market where speed is now a competitive differentiator, incomplete FNOL data can be one of the most expensive bottlenecks in claims operations.
What’s needed is a real-time, integrated view of the claim, the customer and the vehicle — early enough to identify anomalies, inconsistencies and suspicious patterns without disrupting legitimate claims. Leveraging the same data and expertise already used in motor risk assessment can help provide real-time insight at the point of claim. Crucially, in the same way this data is streamlined into the quote process, claims intelligence will be fed directly into the claims process at the points it’s needed most.
A common challenge is that claims teams can often spend time assessing risk factors that should already be known. They can effectively end up focusing on administrative tasks, such as checking vehicle specs, confirming ownership details, validating repair assumptions and identifying ADAS features, rather than problem solving. The immediate focus for claims intelligence at FNOL is therefore on prefilling third party contact details and validating key vehicle attributes, including windscreen features and other vehicle insights including those mentioned above. This will help claims handlers to get on the front foot to validate the details of the claim, spot any risk indicators and guide the claim onto the right path.
The future of claims is workflow-ready intelligence, delivered through APIs
Claims teams are operating in one of the most demanding environments in insurance — balancing speed, accuracy, cost and customer experience, often simultaneously. Without the right connected intelligence, they are being asked to make critical decisions without the full picture.
Through connected claims intelligence, the goal is not to replace human judgement but to strengthen it, giving claims teams the confidence that their early decisions are informed, consistent and defensible.
Closing the gap between underwriting and claims
The insurance market has long treated underwriting and claims as separate disciplines drawing on different data, different systems and different expertise. Two developments are now closing that gap. The first is bringing the data and intelligence already proven in motor underwriting into the claims process. Through solutions such as Vehicle Insights at Point of Claim, Windscreen Check and Claims Datafill, LexisNexis Risk Solutions is enabling access to richer vehicle intelligence at FNOL, alongside insights on windscreen features and prefill of third-party contact details. This is designed to make an immediate and measurable difference to claims teams, ahead of further claims solutions in the coming year.
The second is cross-market claims intelligence. LexisNexis® Precision Claims is a contributory database combining home and motor claims history across the market, which will give insurance providers a fuller picture of an individual's claims experience at both underwriting and claims stage. Together, these developments point to a more connected approach to risk, where data is shared and applied across the insurance lifecycle to support better decision-making.
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