LexisNexis Risk Solutions

Definition

LexisNexis Risk Solutions is a data analytics company that provides identity verification, fraud detection, and risk assessment services to banks, insurers, government agencies, and other organizations, drawing on large proprietary and public-record data assets to help clients confirm who a person is and assess the risk associated with a transaction or application. It operates as part of RELX and is distinct from the LexisNexis legal research product, though both share the same parent company and brand heritage.

Overview

LexisNexis Risk Solutions grew out of the same corporate lineage as the well-known LexisNexis legal research service, but it applies the underlying data-aggregation expertise to a different problem: helping organizations verify identity and assess risk when onboarding a new customer, processing an insurance claim, underwriting a loan, or screening a transaction, using data assets that include public records, historical identity linkage data, and device and behavioral signals collected through its own network. Mechanically, the company's platforms match an individual's submitted information, such as name, address, date of birth, or device fingerprint, against its aggregated data holdings to produce a confidence score on whether the identity is genuine, whether the applicant has a history of fraud or default, or whether a given transaction pattern resembles known fraud typologies. Its risk products span several verticals with purpose-built data models, including insurance risk scoring built from claims history, financial-services risk assessment built from credit and banking-adjacent data, and government-facing identity and eligibility verification services. Within the identity-verification and fraud-analytics landscape, LexisNexis Risk Solutions is often positioned alongside Socure and other identity-verification vendors, but its differentiator is the scale and historical depth of its underlying data assets, built up over decades across insurance, financial services, and public-records domains, compared to newer entrants that have built identity-verification models primarily around document scanning and biometric matching rather than deep historical record linkage. It also overlaps with behavioral fraud-analytics vendors like Featurespace, though Featurespace's core strength is adaptive transaction-behavior modeling rather than identity and public-record matching. In practice, banks use LexisNexis Risk Solutions during account opening to verify applicant identity and screen for synthetic-identity fraud, insurers use its claims-history data to detect staged or exaggerated claims and to price risk more accurately at underwriting, and government agencies use its identity-verification services for benefits eligibility and fraud prevention programs. Its data is also used within broader anti-money-laundering and know-your-customer compliance workflows across regulated industries. Because its value depends heavily on the breadth and currency of its underlying data holdings, its usefulness can vary by geography, being strongest in markets, such as the United States and United Kingdom, where it has built the deepest historical data assets, and comparatively thinner in regions with less established public-record digitization. As with any identity and risk-scoring service, false positives can occur for individuals with thin credit or public-record histories, such as recent immigrants or young adults, requiring supplementary verification methods for those populations.

Key Features

• Large proprietary and public-record data assets spanning decades
• Identity verification scoring for financial services and government
• Insurance claims-history risk scoring and underwriting support
• Synthetic-identity and application fraud detection
• Anti-money-laundering and know-your-customer workflow support
• Device and behavioral signal analysis alongside record matching
• Cross-industry data reach spanning insurance, banking, and public sector

Use Cases

Alternatives

Frequently Asked Questions

Related in Cybersecurity