Overview#
A financial crime investigator staring at 200 rows of transaction data might spend an afternoon identifying a layering scheme. The same data rendered as a transaction graph reveals the structure in seconds: a hub address receiving funds from twenty wallets, dispersing to six more, with one branch looping back through a known mixer. The visual pattern does what tabular data cannot. That is the investigative advantage that graph analytics delivers.
The Blockchain Transaction Graph Analytics platform provides visual network analysis capabilities including graph-based transaction visualisation, multi-hop relationship mapping, and algorithmic pattern detection across blockchain networks. Financial crime investigators, blockchain analysts, AML compliance officers, and forensic accountants use transaction graphs to uncover hidden relationships, trace fund flows, and identify suspicious patterns that would remain invisible in flat transaction records.
Key Features#
- Visual Network Graph Generation: Interactive force-directed graph visualisations with capacity for thousands of nodes, revealing hidden relationships and fund flow patterns critical to financial crime investigations
- Multi-Hop Transaction Tracing: Trace transactions across multiple degrees of separation, following fund flows through intermediary addresses, mixers, and complex layering schemes
- Graph Algorithm Pattern Detection: Applies PageRank, clustering, centrality analysis, and community detection algorithms to identify hub addresses, suspicious structures, and coordinated networks
- Relationship Mapping: Weighted edge analysis showing transaction volume, frequency, and timing between addresses for quantifying relationship strength
- Value Threshold Filtering: Focus on significant fund movements by filtering transactions based on configurable minimum value thresholds
- Interactive Exploration: Drag, zoom, pan, and click nodes for detailed transaction information with drill-down capabilities for deeper investigation
- Cross-Chain Graph Correlation: Link and visualise transaction relationships spanning multiple blockchain networks
- Temporal Flow Animation: Replay fund movements over time to understand the sequence and timing of suspicious activity patterns
Supported Networks#
- Major Blockchains: Bitcoin, Ethereum, Tron, BNB Chain, Solana, Cardano, Polkadot, Avalanche
- Layer 2 Solutions: Polygon, Arbitrum, Optimism, Base, zkSync Era, Starknet, Linea
- EVM-Compatible Chains: Cronos, Moonbeam, Fantom, Gnosis Chain, Aurora, Celo, and more
- UTXO Chains: Bitcoin, Bitcoin Cash, Litecoin, Dogecoin
Graph Analysis Capabilities#
Node Analysis#
- Address classification and entity attribution displayed directly on graph nodes
- Risk-based colouring (green/yellow/orange/red) for immediate visual pattern recognition
- Automatic identification and highlighting of sanctioned addresses and known threat actors
- Node sizing based on transaction volume or balance for quick identification of significant addresses
Edge Analysis#
- Transaction value and frequency displayed on edges connecting addresses
- Directional flow indicators showing movement of funds between nodes
- Temporal edge properties showing when transactions occurred relative to investigation timeline
- Aggregated multi-transaction edges summarising total flow between address pairs
Pattern Detection#
- Hub Detection: PageRank and centrality algorithms identify central addresses in transaction networks
- Community Detection: Clustering algorithms reveal groups of related addresses operating together
- Anomaly Detection: Statistical analysis flags unusual graph structures characteristic of laundering or fraud
- Mixer Identification: Graph topology analysis identifies mixing service interaction patterns
- Exchange Detection: Recognizes centralized exchange deposit and withdrawal patterns in graph structure
Investigation Workflows#
- Start from a single address and expand the graph by following fund flows in any direction
- Add addresses to the graph from external sources: watchlists, intelligence reports, tip-offs
- Save and share graph states for collaborative investigation across team members
- Export graph visualisations for court presentations and forensic reports
Investigation Use Cases#
Ransomware Fund Tracing#
- Visualise the complete path of ransom payments from victim to cash-out
- Identify intermediary addresses, mixing services, and exchange deposit points
- Map the financial infrastructure of ransomware operations through graph expansion
Money Laundering Network Mapping#
- Reveal layering and integration phases through multi-hop graph traversal
- Detect rapid dispersion, reconsolidation, and circular flow patterns
- Identify the ultimate beneficiaries of laundered funds through convergence analysis
Terrorist Financing Analysis#
- Map funding networks from donors through intermediary wallets to operational accounts
- Identify financial facilitation networks through community detection algorithms
- Trace cross-border fund movements through cryptocurrency channels
Fraud Investigation#
- Identify accomplices and beneficiaries in cryptocurrency scam operations through graph expansion
- Detect coordinated wallet networks through community detection and behavioural analysis
- Visualise the distribution of fraud proceeds across multiple addresses and chains
Asset Recovery#
- Locate stolen funds by tracing through transaction graphs to identifiable endpoints
- Generate visual evidence showing fund flow from theft to current location
- Identify exchange and custodial deposit addresses for asset freeze requests
Compliance Investigation#
- Build transaction relationship maps for enhanced due diligence reviews
- Identify indirect connections between customers and high-risk entities
- Generate visual documentation for SAR filings and regulatory examination
Graph Export and Reporting#
- Export graph visualisations as high-resolution images for court presentations
- Generate investigation reports with annotated graph snapshots showing key findings
- Export graph data in structured formats for integration with case management systems
- Create shareable investigation links for collaborative review
Open Standards#
- GraphQL (June 2018 specification): All transaction graph queries, multi-hop traversal operations, and entity expansion requests are exposed through a typed GraphQL API, enabling clients to request precisely the relationship fields and hop depths they need without over-fetching.
- FATF Recommendation 15 (New Technologies) and Recommendation 16 (Travel Rule): Graph-level fund-flow evidence supports Virtual Asset Service Provider obligations by mapping transaction relationships to counterparty entities required for Travel Rule disclosures and suspicious activity reporting.
- ISO/IEC 27037 (Digital Evidence Identification, Collection, and Preservation): Graph construction, expansion, and export activities follow the evidence-handling principles of ISO/IEC 27037, with a complete audit trail for each investigative step to support admissibility in legal proceedings.
- ASTM E2916 (Standard Guide for Examination of Digital and Multimedia Evidence): Graph visualisation exports and annotated transaction-network reports are structured to meet the documentation requirements referenced in ASTM E2916 for forensic examination of digital evidence.
- Bitcoin UTXO Model (BIP Standards): Multi-hop tracing and graph edge construction on UTXO-based chains (Bitcoin, Litecoin, Dogecoin) are grounded in the transaction model defined by Bitcoin Improvement Proposals, correctly handling input aggregation and change-output relationships.
- Ethereum Virtual Machine (EVM) Specification and ERC-20 Transfer Events: Graph edge construction across EVM-compatible chains decodes ERC-20 Transfer events to attribute token flows correctly within transaction networks, using the publicly specified ABI encoding.
- ISO 8601: All timestamps on graph nodes, edges, audit trail entries, and export packages are serialised in ISO 8601 format, ensuring interoperability with case-management, SIEM, and regulatory-reporting systems.
- GDPR (Regulation (EU) 2016/679): Transaction graph data derived from public blockchain records is processed and retained in accordance with GDPR requirements, with appropriate safeguards applied when personal data may be inferred from on-chain activity patterns.
Compliance#
- Graph analysis methodology documented for court admissibility and expert testimony
- Evidence-grade exports with cryptographic verification and chain-of-custody documentation
- Supports Bank Secrecy Act, AML/CTF, and FATF Travel Rule compliance workflows
- Complete audit trail of all graph construction, expansion, and analysis activities
- Supports forensic standards including ISO/IEC 27037 and ASTM E2916
- Role-based access control with investigation-level permissions
- SOC 2 Type II certified infrastructure with GDPR-compliant data handling
Last Reviewed: 2026-02-05 Last Updated: 2026-04-14