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KYT: Know Your Transaction

Definition

Know Your Transaction (KYT) refers to the ongoing monitoring and analysis of financial transactions by institutions, payment service providers, virtual asset service providers, and other regulated entities to detect unusual, suspicious, or high-risk activity indicative of money laundering, terrorist financing, fraud, or other financial crime.

It goes beyond customer or business identification (such as KYC or KYB) to scrutinise the actual movement of funds.

In an AML/CFT framework, KYT enables institutions to “follow the money” in real time or near real time, identifying anomalies, patterns of risk exposure, and behavioural changes that may require investigation or reporting.

Explanation

While Know Your Customer (KYC) and Know Your Business (KYB) establish baseline identity and profiling,

KYT focuses squarely on the transactional behaviour of customers, counterparties, and systems.

It involves collecting transaction data (including originator, beneficiary, amount, currency, channel, geolocation, and purpose), applying rules and analytics, and determining whether a given transaction or sequence of transactions raises red flags.

KYT is integral to modern AML/CFT strategies because:

  • Fraudsters and money launderers increasingly exploit anonymous or remote channels, making identity checks alone insufficient.
  • Transaction flows may reveal misuse of accounts, layering, circular movements, mule activity, or transfers to sanctioned or high-risk jurisdictions.
  • Regulators emphasise transaction monitoring as a core control in digital, correspondent banking, trade finance, and virtual asset contexts.
  • The combination of identity-based (KYC) and transaction-based (KYT) controls creates richer intelligence and supports risk-based decision making.

In practice, KYT is realised through rules engines, behavioural analytics, real-time streaming data, machine learning models, alerts, and case management workflows.

It is both preventive (blocking or holding transactions) and detective (flagging for investigation or reporting).

For a robust AML/CFT programme, KYT must be aligned with the institution’s risk appetite, typologies, regulatory requirements, and operational capacity.

KYT in AML/CFT Frameworks

Within AML/CFT frameworks, KYT plays a critical role across multiple domains:

Customer/Transaction Risk Assessment

Financial institutions use KYT insights to calibrate risk ratings and segment customers based on transactional behaviour.

A customer with a normal profile but irregular transaction patterns may shift to a higher risk band.

  • Continuous review of customer transactional history and deviation from expected behaviour.
  • Integration of transaction scoring into ongoing due diligence and enhanced due diligence (EDD) workflows.
  • Calibration of rules based on customer risk, product risk, and jurisdictional risk.

Transaction Monitoring and Alerts

KYT provides the automated backbone for transaction monitoring systems.

It includes:

  • Real-time or near-real-time screening of transactions against internal and external criteria.
  • Application of rules such as velocity thresholds, ledger hopping, structuring, high-risk corridor transfers, and rapid pass-through patterns.
  • Generation of alerts that feed into case management and investigations.

Sanctions, PEPs, and Watch-list Integration

KYT ensures that transactions involving sanctioned entities, politically exposed persons (PEPs), high-risk countries, or prohibited items are identified at the transaction level:

  • Monitoring of both originator and beneficiary data for match against watch-lists.
  • Flagging of unusual counterparty relationships or emerging network exposures.
  • Automatic escalation or blocking of transactions where regulatory obligations demand immediate action.

Virtual Assets and Emerging Channels

With the growth of cryptocurrencies, digital wallets, embedded finance, and fintech platforms, KYT has become increasingly relevant:

  • Tracking transfers on blockchains, analysing wallet addresses, detecting mixing services, or chain hops.
  • Monitoring peer-to-peer transfers, token flows, decentralised finance (DeFi) interaction,s and initial coin offerings (ICOs).
  • Integrating transaction monitoring across multiple channels to detect cross-platform misuse.

Key Components of KYT

The operational architecture of KYT involves several core components:

Data Collection and Integration

A robust KYT system must ingest and consolidate data from multiple sources:

  • Customer profile and KYC/KYB data.
  • Transaction details from internal systems (payments, transfers, card, accounts).
  • External data (sanctions, adverse media, risk lists, merchant data).
  • Behavioural and device data (for digital channels).
  • Blockchain or virtual asset ledger data (for VASPs).

Rules, Analytics, and Scoring

Transactions are evaluated using logic, analytics, and machine learning:

  • Pre-defined rules based on typologies (e.g., structuring, layering, trade-based money laundering).
  • Velocity and anomaly thresholds (e.g., large amounts, rapid transfers).
  • Scoring models that assign risk ratings to transactions, customers, or counterparties.
  • Behavioural analytics to detect deviations from expected patterns and peer group behaviour.

Decision and Action

Based on the score and rules outcome, an institution may:

  • Allow the transaction to proceed.
  • Automatically hold or block the transaction pending review.
  • Generate an alert forwarded to compliance/investigation teams.
  • Trigger enhanced due diligence or customer-relationship review.
  • Report suspicious transactions to the financial intelligence unit (FIU).

Governance, Monitoring, and Feedback

Effective KYT programmes ensure oversight and continuous improvement:

  • Rule library governance, rule-change tracking, and version control.
  • Monitoring of false positive/false negative rates and tuning of rules.
  • Periodic review of typologies and emerging risk trends.
  • Reporting to senior management on performance, trends a,nd residual risk.

Examples of KYT Scenarios

Here are several typical scenarios where KYT is applied:

  • A customer with an account normally used for domestic salary transfers suddenly initiates frequent high-value international transfers to high-risk jurisdictions.
  • A corporate client starts receiving funds from unrelated parties and quickly wires them onward to different accounts within hours (pass-through behaviour).
  • A digital wallet address receives funds from a known mixing service or hacking-dump origin, then disperses the funds across multiple wallets.
  • A series of card transactions just below the threshold across multiple merchant categories and locations, suggesting structuring or layering.
  • A trade finance transaction where the invoice value is significantly higher than the underlying shipment value, with subsequent fund disbursement to shell entities.

Impact on Financial Institutions

Implementing KYT correctly yields benefits but also presents challenges:

Benefits

  • Improves detection of sophisticated money-laundering and terrorist-financing typologies.
  • Enables faster response and more effective blocking of high-risk transactions.
  • Reduces the overall cost of investigations by automating first-line detection.
  • Enhances audit trail, regulatory compliance evidence, and internal transparency.
  • Strengthens customer trust, particularly in digital and cross-border channels.

Challenges

  • A high volume of transaction alerts may lead to overwhelming false positives if rules are poorly calibrated.
  • Complex data integration across legacy systems and new channels demands significant investment.
  • Machine learning models require training, ongoing tuning, and handling of bias
  • Emerging channels (e.g., crypto, DeFi) introduce new typologies and data-structure complexities.
  • Governance is essential to ensure rules remain relevant, accurate, and aligned with emerging threats.

Challenges in KYT Implementation

Effective implementation of KYT requires addressing several common obstacles:

  • Defining accurate thresholds and typologies that reflect actual risk patterns, not generic rules.
  • Ensuring data completeness and quality, particularly for cross-border or virtual-asset transactions.
  • Integrating systems across payment types, virtual assets, and legacy banking environments.
  • Balancing detection sensitivity with customer experience (avoiding unnecessary holds or blocks).
  • Keeping pace with evolving typologies, such as account takeover, mule networks, and layer-obfuscation techniques.

Regulatory Oversight & Governance

International Standards

Global regulators recognise transaction monitoring as a critical component of AML/CFT frameworks.

Entities such as the Financial Action Task Force (FATF) emphasise the need for risk-based monitoring, real-time screening, and the obligation to report suspicious transactions.

National Regulators and Supervisory Authorities

Financial institutions are required by national AML laws to deploy transaction monitoring systems, file suspicious transaction reports (STRs), and maintain audit-ready records of monitoring and investigations.

Supervisory bodies expect documentation of rule governance, tuning activities, and performance indicators.

Internal Governance

A strong KYT programme demands oversight from senior management and the board, alignment with risk appetite, clear escalation paths, transparent reporting, and continuous tuning.

Internal audit functions assess whether KYT controls are functioning as intended and whether hypotheses/rules remain relevant.

Importance of KYT in AML/CFT Compliance

KYT is indispensable for financial crime prevention in modern financial services. It enables institutions to move from reactive compliance (solely identity-based checks) to proactive controls that monitor and intervene in transactional flows. Effective KYT contributes to:

  • Closing gaps in AML/CFT programmes by linking customer behaviour to actual transaction risk.
  • Supporting real-time intervention, blocking illicit flows, and reducing time-to-action.
  • Strengthening risk-based resource allocation (compliance teams can focus on high-risk alerts).
  • Meeting regulatory expectations for dynamic monitoring, reporting, and continuous improvement.
  • Maintaining an audit trail of decisions, rule changes, and investigations that enhances governance.

As the financial crime landscape evolves, with virtual assets, embedded finance, open banking, and fintech innovations, KYT remains the cornerstone of dynamic, intelligence-led AML/CFT frameworks.

Related Terms

  • Transaction Monitoring
  • Suspicious Transaction Reporting (STR)
  • Enhanced Due Diligence (EDD)
  • Sanctions Screening
  • Behavioural Analytics
  • Virtual Asset Service Providers (VASPs)
  • Rule-Based Detection Engines

References

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