Link analysis

Link analysis is a data analysis technique that evaluates relationships between nodes—such as people, accounts, transactions, or devices—to uncover hidden patterns, networks, or anomalies. It's widely used in cybersecurity, fraud detection, law enforcement, and social network analysis.

About Link analysis

How does link analysis work in fraud prevention?

Link analysis visually maps and quantifies how entities are connected, often using graph databases. For example, it can reveal that multiple customer accounts use the same phone number, IP address, or payment method—suggesting coordinated fraud. Analysts can detect fraud rings, collusion, and synthetic identity clusters that would be difficult to find using linear data review alone.

What are practical applications of link analysis?

Beyond fraud, link analysis is used in anti-money laundering (AML) to track the flow of funds, in cybersecurity to detect malware propagation across systems, and in law enforcement to map criminal networks. It also has applications in marketing (customer segmentation), healthcare (disease tracking), and even counter-terrorism.

What are the challenges in implementing link analysis?

The biggest challenge is data integration—bringing together structured and unstructured data from multiple sources to build accurate relationships. Poor data quality can lead to false positives or missed connections. Scaling link analysis to millions of nodes in real-time is also technically complex, requiring graph databases and advanced visualization tools. Additionally, interpreting the resulting graphs often requires skilled analysts with domain expertise.

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