RELX: Risk Business Services Seminar - Deep Data Differentiation

Research evidence excerpt

RELX: Risk Business Services Seminar - Deep Data Differentiation

IdeaMoperate more efficiently by using advanced data and analytics to build a detailed

view of consumers and businesses, allowing them to assess trust and risk in real

time.

…each leveraging the multi-layered LexisNexis Risk Intelligence Network. At the

core of Business Services, is the LexisNexis Risk Intelligence Network, a data-and-

analytics engine built from public records, licensed third-party data, customer-

contributed data, as well as RELX proprietary and derived data. Management

highlighted that the Risk segment overall has 25+ contributory and proprietary

databases, with 10 residing in Business Services; these customer-contributed data

signals are described as "a significant contributor and significantly differentiated".

The network operates at substantial scale (covering virtually all US adults,

processing over 1 trillion sanctions screenings and around 145 billion digital

transactions annually), transforming the large sums of data using analytics and AI

into risk signals and scores. These checks are often performed in tens of

milliseconds. As more transactions and outcomes flow through the network, the

data becomes richer, creating a compounding network effect that improves

detection of emerging risk patterns and strengthens customer value over time.

During the product demonstration, the company also showed how the network

links signals such as email addresses, devices, payment cards, billing details, and

behavioral patterns to build connected digital identities. This helps identify unusual

changes, such as a new device, unfamiliar location, or signs of coercion, and

distinguish trusted activity from potential fraud.

Management see little AI disintermediation risk to Business Services. AI was