By Helen Richardson, Insurance senior product manager, U.K. and Ireland, LexisNexis Risk Solutions
Robust risk assessment
Best practice and robust risk assessment requires clean and accurate customer data. The challenge is that many insurance providers continue to face challenges in maintaining accurate, up-to-date, and complete customer records. It’s not just the sheer volume of customer data they maintain, but mergers and acquisitions bring new customer datasets to integrate. Consumer information can quickly become outdated, while siloed systems across products, platforms, and business units make it even harder to reconcile identities to uncover fact from fiction.
Uncovering anomalies
Customer data needs to be linked and matched accurately so that anomalies in current applications or claims can be detected quickly to help identify possible fraud. Countering fraud is not the only benefit - by resolving the data held on a customer, insurance providers gain a better understanding of the relationship with that individual for more informed decisions across the board and opportunities to offer additional products. It gives them the power to create the ‘single customer view’, improving decision-making at key moments like quotes, claims, and renewals.
Customer data linking solutions
As the investment in AI solutions to better serve their customers grows, clean customer data becomes more business critical to insurance companies than ever. Recognising this need, some insurance companies are investing in automated identity resolution and customer data linking solutions. Others are developing their own data matching capabilities in-house, although this can be limited by the depth and breadth of their own customer data.
Foundational step for the Single Customer View
The power of data linking solutions such as LexID® for Insurance is in how it can match an insurance provider’s data to a unique individual LexID, leveraging a suite of external datasets, to create a consistent, more accurate, and real-time view of each customer across the insurance lifecycle —without the burden of building and maintaining internal systems. A higher match and resolution rate can be achieved by using data from multiple sources beyond a single insurer’s database.
This approach to data matching and linking can give insurance providers a foundation to enable cleaner, more structured data to enhance operational efficiency and also lay the foundations for AI readiness, as covered in our article for the January 2025 issue of Actuarial Post .
Uncovering hidden fraud
From a fraud detection perspective, by linking fragmented records across policies, claims, and underwriting to create a unified customer identity, risk assessment can be enhanced throughout the customer lifecycle. Hidden fraud networks can be identified by linking claims, policyholders, and third parties across different records while hidden fraud patterns, duplicate policies, and suspicious claims can be uncovered through data linking across business lines.
For example, it should become immediately apparent that a ‘Mr. Brown’ applying for a home insurance policy has had a series of repudiated motor claims at a previous address or that ‘Mrs. Smith’s’ new home insurance claim contradicts the information provided for a pet insurance claim. This improves match accuracy and also helps prevent fraud. With greater insight into fraud risks, insurance providers may also choose to build their own fraud detection models.
Data linking and resolution for more informed decisions
Data linking engines should have the capacity to work at scale across insurance workflows but must also adapt to different customer workflows—whether in real-time, batch processing, or exception file handling. Ultimately, the ‘win’ for insurance providers is using identity linking for instant decision-making by enabling these organisations to harness the full power of their own customer data, and the benefits can span pricing, underwriting and claims platforms throughout the customer lifecycle.
Many insurance providers are on a mission to create a Single Customer View, not least for the insights this view will offer for fraud detection. Data linking engines now give them this power, linking previously siloed datasets across the business, helping insurance providers make more informed decisions to protect themselves and their customers from fraud and continue to offer the best experience and products.
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