API Marketplace

Solutions

Resources

Our Company

← Back to Glossary

Graph Analytics

Overview

Graph analytics models entities and their relationships as nodes and edges to surface patterns traditional tables miss. In AML and fraud, it reveals money mule networks, collusive merchants, and shared infrastructure such as devices, IPs, or beneficiaries. Techniques include community detection, centrality, path analysis, and subgraph matching against typologies. Integrated with entity resolution and funds-flow data, graphs power alert grouping, prioritize high-impact clusters, and support decisive actions like coordinated closures.

Governance must track data lineage, limit sensitive attributes, and document thresholds to avoid over-linking. Effective deployments pair dashboards for analysts with model feedback loops, ensuring insights translate into tuned scenarios and reduced false positives. Graphs also strengthen SAR narratives by providing clear visual timelines and connections.

Stay ahead of risk with Signzy

Explore tools that help you onboard, monitor, and verify with confidence

One Touch KYC

Launch global KYC flows with built-in document OCR, liveness checks, deepfake detection, and AML, all through a single, customizable dashboard.

Database Verification

Instantly verify user information by connecting to trusted databases across jurisdictions for accurate, compliant, and faster onboarding.

Biometric Verification

Authenticate users with facial, fingerprint, and liveness biometrics powered by AI to prevent identity spoofing and fraud.

Related Terms

Link Analysis

Funds Flow Analysis

Network Risk Signals

FAQ

Which links are most reliable?

Durable signals such as device fingerprints, funding accounts, shared beneficiaries, and verified corporate ties outperform weak attributes like transient IPs alone.

How does it reduce alert noise?

Grouping related alerts into network cases shows context, prevents duplicate work, and highlights the central actors to act on first.

What skills do analysts need?

Familiarity with graph concepts, playbooks for pattern interpretation, and tools to pivot between nodes, transactions, and case evidence quickly.

Any fairness concerns?

Yes. Avoid over-linking based on low-quality signals, record provenance, and require human review for impactful actions.