Overview#
A compliance analyst at a cryptocurrency exchange reviewed hundreds of flagged transactions each week, most of them false positives from a rules-based system tuned so broadly it caught everything. After switching to AI-powered risk scoring, the same analyst handled a fraction of that volume. The model had learned to distinguish a high-volume OTC desk from a structuring operation, a DeFi power user from a mixer operator. Fewer alerts, better cases, faster decisions.
The Blockchain AI Risk Scoring system delivers real-time, AI-powered risk assessment across blockchain transactions and addresses. Combining behavioural pattern analysis, anomaly detection, and predictive modelling, it identifies high-risk entities before they complete suspicious transactions. AI models outperform traditional rule-based systems in both detection accuracy and false positive reduction, making them the practical choice for AML compliance teams, financial intelligence units, and exchange compliance officers operating at scale.
Key Features#
- Multi-Factor Risk Evaluation: Assesses distinct risk factors across seven categories: transaction patterns, address reputation, counterparty associations, temporal behaviours, cross-chain activities, token characteristics, and historical compliance violations
- AI-Powered Detection: Machine learning models continuously adapt to evolving threat patterns, incorporating feedback from global sanctions lists, known threat actor addresses, and real-time behavioural anomalies
- Predictive Early Warning: Predictive models identify emerging threats before the first suspicious transaction, enabling proactive intervention
- False Positive Reduction: Behavioural analysis eliminates the majority of false alerts compared to traditional rule-based methods
- Real-Time Scoring: Enterprise-grade performance with low-latency global scoring capability for high-volume transaction environments
- Dynamic Risk Categories: Scores map to actionable risk tiers (Critical, High, Medium, Low, Minimal) with configurable thresholds for organisational risk tolerance
- Explainable Scoring: Every risk score includes a detailed breakdown of contributing factors, enabling transparent compliance decisions and audit documentation
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
- Additional Networks: Ripple, Stellar, Algorand, Cosmos, Near, Tezos, Aptos, Sui
Investigation Use Cases#
Transaction Screening#
- Score every incoming and outgoing transaction in real-time before processing
- Apply risk-based transaction limits and controls based on dynamic scoring
- Automatically escalate high-risk transactions for manual compliance review
Customer Risk Assessment#
- Generate risk profiles for customer wallet addresses during onboarding
- Continuously update risk scores as customer transaction behaviour evolves
- Trigger enhanced due diligence workflows when risk thresholds are breached
Sanctions Compliance#
- Incorporate global sanctions list data from OpenSanctions and OFAC into risk scoring for immediate detection
- Identify indirect sanctions exposure through counterparty association analysis
- Generate compliance documentation showing risk assessment basis for each decision
Threat Intelligence#
- Detect addresses associated with ransomware, darknet markets, and fraud operations through behavioural pattern matching
- Identify mixer and tumbler usage as risk indicators for potential money laundering
- Flag cross-chain bridge activity combined with other risk factors as potential evasion behaviour
Portfolio Risk Management#
- Aggregate risk scores across address portfolios for enterprise-level risk visibility
- Monitor risk score trends over time to identify deteriorating risk profiles
- Generate risk reports for board-level oversight and regulatory examination
Risk Score Categories#
- Critical (90-100): Immediate action required; direct sanctions matches, confirmed ransomware patterns, or active exploit indicators
- High (70-89): Manual review required; significant counterparty risk, mixer usage, or multiple risk factor convergence
- Medium (40-69): Enhanced monitoring recommended; moderate risk indicators requiring ongoing observation
- Low (20-39): Standard processing with logged risk indicators for trend analysis
- Minimal (0-19): Normal processing; no elevated risk factors detected
Open Standards#
- FATF Recommendations (Risk-Based Approach): The risk-scoring methodology is explicitly documented to exceed FATF standards for risk-based supervision of virtual asset service providers, and supports FATF Recommendation 16 (Travel Rule) compliance workflows for transaction monitoring.
- OpenSanctions FollowTheMoney (FtM) Format: Sanctions screening ingests nightly bulk data from OpenSanctions in the FollowTheMoney newline-delimited JSON format, covering OFAC, EU, UN Security Council, UK HMT, and other consolidated lists.
- OFAC Specially Designated Nationals (SDN) List: The OFAC SDN list is a first-class data source screened against every address and counterparty, with direct source-code mapping for all OFAC dataset variants.
- ERC-20 / ERC-721 / ERC-1155 (Ethereum Improvement Proposals): Token transfer events conforming to these Ethereum token standards are parsed and classified natively, enabling risk assessment of fungible, non-fungible, and multi-token contract interactions.
- GraphQL (June 2018 Specification): All risk scoring, wallet attribution, clustering, and forensic report queries and mutations are exposed through a GraphQL API built on the Strawberry schema library.
- Bank Secrecy Act (BSA) / Suspicious Activity Reports: The financial transaction model includes a Suspicious Activity Report (SAR) entity, and the module explicitly supports BSA transaction monitoring and reporting compliance workflows.
- JSON Web Tokens (RFC 7519 / OAuth 2.0): Service-to-service authentication across the risk-scoring pipeline uses signed JWTs, and all API queries require an authenticated OAuth 2.0 bearer context.
Compliance#
- Risk scoring methodology documented for regulatory audit and examination
- Exceeds FATF standards for risk-based approach to virtual asset supervision
- Supports AML/CTF program requirements for transaction monitoring
- Supports Bank Secrecy Act and FATF Travel Rule compliance workflows
- Complete audit trail of all risk assessments, score changes, and resulting actions
- Scoring transparency enables compliance teams to explain and defend risk decisions
- SOC 2 Type II certified infrastructure with GDPR-compliant data handling
Last Reviewed: 2026-02-05 Last Updated: 2026-04-14