LexisNexis Relationship Mapping
E-commerce fraud protection software
E-commerce software
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What is LexisNexis Relationship Mapping
LexisNexis Relationship Mapping is a fraud and identity risk analysis capability that visualizes and analyzes connections between identities, devices, accounts, and transactions to support investigations and decisioning. It is used by fraud operations, risk teams, and investigators to identify organized fraud patterns, synthetic identities, and account takeover activity across digital commerce and financial workflows. The product emphasizes link analysis and network visualization to surface hidden relationships that may not be evident in single-transaction scoring. It is typically deployed alongside other LexisNexis Risk Solutions data and analytics services rather than as a standalone e-commerce platform.
Network link analysis visibility
Provides graph-style visualization of relationships among entities such as consumers, accounts, devices, addresses, and transactions. This helps analysts identify clusters, mule networks, and repeat infrastructure that can indicate organized fraud. It complements point-in-time scoring by enabling case-driven exploration and hypothesis testing. The approach is well-suited to complex fraud patterns that span multiple accounts or channels.
Investigation and case support
Supports fraud operations workflows where analysts need to explain why activity is suspicious and document findings. Relationship views can accelerate triage by highlighting shared attributes and unusual linkages. This can reduce manual cross-referencing across disparate systems when investigating chargebacks, account takeover, or synthetic identity behavior. The output is generally more interpretable for investigators than black-box model results alone.
Integrates with risk data assets
Aligns with LexisNexis Risk Solutions’ broader identity and fraud data ecosystem, enabling enrichment from identity, device, and digital intelligence sources where licensed. This can improve coverage when organizations already use other LexisNexis fraud and identity products. Integration can support consistent entity resolution across tools, which is important for reliable relationship mapping. It can be used as an analytic layer on top of existing fraud signals.
Not a full commerce suite
Despite being applicable to online orders and digital transactions, it is not an e-commerce platform for storefront, catalog, checkout, or order management. Organizations still need separate commerce and payments tooling to run online sales. The product’s value is primarily in risk analysis and investigation rather than end-to-end e-commerce operations. Buyers evaluating it under “e-commerce software” may find functional gaps outside fraud use cases.
Data dependency and licensing
Relationship mapping quality depends on the breadth and freshness of underlying data sources and the organization’s ability to provide identifiers and event data. Some enrichment sources may require additional licensing, contractual approvals, or regional availability checks. If input data is sparse or inconsistent, the resulting network may be incomplete or noisy. This can limit effectiveness for new programs without established data pipelines.
Operational complexity for teams
Graph-based investigation tools typically require analyst training to interpret links, avoid false associations, and build repeatable workflows. Implementation often involves integration work (APIs, data normalization, entity resolution rules) and governance around access to sensitive identity data. Smaller teams may find the operational overhead higher than simpler, fully managed fraud decisioning services. Ongoing tuning may be needed to align outputs with internal fraud policies.
Seller details
LexisNexis Risk Solutions
Alpharetta, Georgia, USA
1997
Subsidiary
https://risk.lexisnexis.com/
https://x.com/LexisNexisRisk
https://www.linkedin.com/company/lexisnexis-risk-solutions/
