BUILT-IN NETWORK ANALYSIS

See the Network Behind the Transactions

Centrality measures, community detection, path tracing, and risk propagation — built into the same engine that monitors your transactions. No graph database. No separate product. No additional licensing.

See Network Analysis Live →

The Graph Database Problem

Most AML platforms require a separate graph database for network analysis — adding cost, complexity, and months of integration. EyesClear takes a different approach.

Separate Graph Database

$100K–$300K+ annual licensing (Neo4j, TigerGraph)
6–12 months to integrate with your AML platform
Permanent data sync pipeline to maintain
Specialized query languages (Cypher, GSQL, Gremlin)
Separate tool for investigators — context switching
Historical re-analysis requires data re-ingestion
vs

EyesClear Built-In

Included in the platform — $0 additional licensing
Available from day one — no integration project
Networks built automatically during transaction processing
Interactive visual interface — no query language needed
Same interface as alerts, cases, and search
Retroactive analysis via overnight reprocessing

What Network Analysis Catches

These typologies are invisible to rule-based transaction monitoring. Network analysis detects them by revealing the structure behind the transactions.

Layering Schemes

Funds split across 15+ accounts, no single transaction exceeds thresholds, but path analysis reveals the complete origin-to-destination flow through every intermediary.

Path Analysis Flow Visualization

Money Mule Networks

30 accounts processing small amounts, individually invisible. Community detection identifies the cluster — shared counterparties, synchronized timing, coordinated patterns.

Community Detection Temporal Analysis

Sanctions Evasion

A sanctioned entity transacts through 4 layers of intermediaries. Direct screening finds nothing. Network path tracing reveals the connection in seconds.

Path Tracing Risk Propagation

Hub-and-Spoke Laundering

A central account collects from dozens of sources, distributes to dozens of recipients. Centrality measures surface it automatically, even with a legitimate cover story.

Centrality Measures Degree Analysis

Fraud Rings

Coordinated accounts that open in clusters, transact with each other, and exhibit mirrored behavior. Community detection and temporal analysis expose the ring structure.

Clustering Anomaly Detection

Trade-Based Laundering

Over/under-invoicing between related entities across jurisdictions. Network analysis reveals the relationship structure and abnormal value flows between them.

Cross-Border Analysis Value Flow

The Analytics Engine

Four classes of network analytics running natively on PostgreSQL. No graph database. Full analytical depth.

📊

Centrality Measures

Identify structurally important accounts in the transaction network.

  • Degree centrality — most connected accounts
  • Betweenness centrality — accounts bridging clusters
  • Closeness centrality — short paths to all others
  • PageRank — importance by transaction flow
🔗

Community Detection

Surface tightly connected groups that transact primarily with each other.

  • Modularity optimization algorithms
  • Hierarchical clustering — multi-level structure
  • Temporal communities — formation and evolution
  • Cross-community flows — boundary transactions
🛤️

Path Analysis

Trace complete fund flows between any two entities across any number of hops.

  • Multi-hop transaction chain tracing
  • Circular flow detection (round-tripping)
  • Shortest path identification
  • Intermediary layer counting
⚠️

Risk Propagation

Calculate how risk spreads through the network based on structure and flow.

  • Network-position-based risk scoring
  • Counterparty risk propagation models
  • Isolation metrics — accounts avoiding detection
  • Velocity analysis — speed of money movement

Investigation-Ready Visualization

Not just analytics — a visual investigation environment where compliance officers explore networks interactively and document findings in real time.

🔍

Interactive Exploration

Click any entity to expand its network. Zoom, pan, and filter in real time.

⏱️

Time Animation

Watch networks form and evolve over days, weeks, or months.

📏

Proportional Nodes

Node size by volume. Edge thickness by amount. Patterns visible instantly.

🎯

Anomaly Highlighting

Unusual patterns and high-centrality nodes are visually emphasized.

🏷️

Dynamic Filtering

Filter by time range, amount, entity type, or risk score on the fly.

📋

Case Integration

Export network findings directly into case management for documentation.

The Cost of Network Analysis

Graph DB Approach EyesClear Built-In
Graph database license $100K–$300K/year $0 — not needed
Integration project $75K–$200K $0 — already built in
Ongoing sync maintenance $30K–$80K/year $0 — same data layer
Specialized staff $120K–$180K/year (graph DBA) $0 — standard PostgreSQL
Time to first investigation 6–12 months after AML go-live Day 1
3-year total cost of network analysis $600K–$1.2M+ Included

4

Centrality measures

Real-Time

Network construction

$0

Additional licensing

Day 1

Available from go-live

0

Graph databases required

See the Networks Your Current System Misses

Live demo on real transaction data. Centrality, communities, paths, and risk propagation — all without a graph database.