Know Your Transaction (KYT)

KYT solutions assign a risk score to each transaction as it occurs, based on a dynamic analysis of on-chain patterns. This involves evaluating factors like:

• Counterparty risk (e.g., wallet associated with sanctions, mixers, or stolen funds)
• Transaction patterns (e.g., structuring, rapid movement through multiple addresses)
• Asset-specific risks (e.g., privacy coins, newly minted tokens) Scores trigger automated alerts or actions, such as blocking, flagging for review, or allowing the transaction.

This feature continuously screens transaction participants against global watchlists and proprietary threat intelligence. It goes beyond simple list-matching to identify:

• Direct and indirect exposure to sanctioned addresses or entities.
• Clustered addresses belonging to the same malicious actor using heuristic and graph analysis.
• High-risk jurisdictions and VASPs (Virtual Asset Service Providers) based on regulatory data. Screening is applied to both the origin and destination of funds.

KYT establishes a baseline of normal activity for wallets or users and flags deviations indicative of financial crime. Key patterns monitored include:

• Structuring (Smurfing): Breaking large transactions into smaller amounts to avoid thresholds.
• Layering: Rapid, complex movement of funds across multiple addresses or chains to obscure origin.
• Funding Patterns: Unusual inflows from high-risk sources like mixers or gambling dApps. This analysis uses machine learning models to adapt to evolving typologies.

KYT automates the creation of a defensible audit trail for compliance. Core capabilities include:

• Suspicious Activity Report (SAR) generation with pre-populated blockchain evidence.
• Recordkeeping of all risk assessments, decisions, and alerts for a specified retention period.
• Regulatory alignment with frameworks from the Financial Action Task Force (FATF), FinCEN, and other global bodies. This creates a reproducible process for examiners and demonstrates a risk-based approach to compliance.

Modern KYT solutions monitor activity across multiple blockchain networks and asset types, recognizing that illicit finance is chain-agnostic. This involves:

• Native support for Bitcoin, Ethereum, and other major Layer 1 and Layer 2 networks.
• Token-standard analysis for ERC-20, ERC-721, and other digital assets.
• Cross-chain bridge monitoring to track funds moving between ecosystems. Coverage extends to DeFi protocols, NFT marketplaces, and on-chain derivatives to provide a holistic view of risk.

Institutions implement their specific risk appetite through customizable rule engines. This allows compliance teams to:

• Define thresholds for transaction amounts, velocity, or geographic exposure.
• Create whitelists and blacklists for trusted or prohibited counterparties.
• Set automated workflows that route high-risk alerts for review or trigger immediate intervention. Rules can be updated in real-time to respond to new threat intelligence or internal policy changes.

KYT systems must ingest and standardize data from multiple sources, including on-chain data (block explorers, node APIs) and off-chain intelligence (threat feeds, sanctions lists). Key challenges include:

• Parsing diverse transaction formats across different blockchains.
• Handling the sheer volume and velocity of blockchain data.
• Normalizing wallet addresses and transaction hashes into a consistent schema for analysis.

Transaction risk is assessed using predefined rules and behavioral heuristics. This involves:

• Pattern Recognition: Identifying known illicit patterns like peel chains, mixer interactions, or rapid fund dispersion.
• Risk Scoring: Assigning scores based on factors like counterparty risk, asset type, and transaction history.
• False Positives: A major challenge is tuning rules to minimize false alerts without missing genuine threats, requiring continuous refinement.

A core analytical task is linking multiple addresses to a single entity or service. This is critical for understanding transaction flows but is technically complex.

• Techniques include common input ownership heuristics and analyzing deposit/withdrawal patterns to centralized services.
• Sophisticated actors use techniques like address rotation and transaction batching to obfuscate these links, making clustering an ongoing adversarial challenge.

For effective compliance, KYT must evaluate transactions in near real-time, often before block confirmation (mempool monitoring). Technical demands include:

• Low-latency data ingestion pipelines.
• High-throughput stream processing engines.
• The trade-off between analysis depth and speed, where more complex risk models increase latency.

KYT operates in a landscape with conflicting pressures:

• Regulatory Push: Mandates for stricter monitoring of DeFi, NFTs, and cross-chain bridges.
• Privacy Tech: The rise of zero-knowledge proofs and privacy-preserving protocols (e.g., Aztec, Tornado Cash) can obscure transaction details, creating blind spots for traditional KYT heuristics.
• Balancing effective monitoring with the pseudonymous nature of public blockchains is a fundamental design challenge.

Modern asset flows span multiple ecosystems, complicating monitoring.

• Bridges & Wraps: Tracking assets as they move between chains via bridges (e.g., Wormhole) or are wrapped (e.g., wBTC).
• Layer-2 Rollups: Monitoring activity on Optimistic Rollups and ZK-Rollups requires understanding their unique data availability and finality characteristics.
• A holistic risk profile requires correlating activity across these fragmented environments.

Know Your Customer (KYC) is the process of verifying the identity of a client at the point of account onboarding. KYT complements KYC by providing ongoing monitoring of the client's transaction behavior after they are onboarded.

• Onboarding vs. Ongoing: KYC is the initial identity check; KYT is continuous activity monitoring.
• Holistic View: Together, they form a complete customer due diligence (CDD) profile: who the user is (KYC) and what they do (KYT).
• Critical for VASPs: Regulated Virtual Asset Service Providers (VASPs) are required to implement both.

Wallet Screening & Clustering are the analytical techniques underpinning KYT. Screening checks individual addresses against risk databases, while clustering uses heuristic and machine learning models to group addresses controlled by a single entity.

• Heuristic Analysis: Groups addresses based on common input ownership, fund consolidation, and smart contract interactions.
• Exposing Bad Actors: Crucial for identifying the full scope of wallets controlled by a mixer service, darknet market, or scam operation.
• Foundation for Risk Scoring: The accuracy of entity clustering directly impacts the precision of a KYT system's risk assessments.