Transaction Monitoring for Real-Time Payments: Designing Controls for Speed

Manish Kumar is a Senior Analyst II at AML RightSource. We encourage our team members to share their insights and expertise by contributing to our content library.

Real-time payment systems are transforming the way money moves around the world. Customers now expect payments to settle in seconds, not days. While this shift creates convenience and efficiency, it also introduces new risks. For compliance professionals, the challenge is clear: how do we design transaction monitoring controls that keep pace with real-time speed, without compromising effectiveness?

Why This Topic Matters

Real-time payment systems are transforming financial services. Faster transactions create better customer experiences and open doors to fraud and money laundering risks. Traditional anti-money laundering (AML) controls often rely on batch processing, which doesn’t fit real-time environments.

This blog explores how to design effective transaction monitoring for instant payments—without sacrificing speed.

Understand the Real-Time Challenge

Real-time payments settle in seconds. Fraudsters exploit this speed because it’s almost impossible to recover once money moves. Monitoring must shift from reactive to proactive. Controls need to detect unusual activity before or immediately after payment authorization.

While working on a case, I encountered a scenario where a fraudster used stolen credentials to access a new account and attempted a high-value transfer via a real-time payment network. The funds were quickly split across several mule accounts. Because we had proactive monitoring rules tied to KYC data and device signals, the system flagged the transaction instantly, allowing us to stop it before settlement and prevent a significant loss.

Apply Risk-Based Segmentation

Not all transactions carry the same level of risk. Real-time monitoring should prioritize higher-risk scenarios — such as cross-border transfers, transactions from new accounts, or unusual spikes in activity. Dynamic thresholds allow systems to flag outliers without overwhelming analysts with false positives.

Introduce Pre-Transaction Risk Scoring and Integration with KYC Data

A strong monitoring system connects directly with a customer’s profile. Knowing who the customer is, their typical transaction behaviour, and risk rating allows alerts to be more precise. This integration helps reduce noise and ensures analysts focus on meaningful alerts.
Instead of relying solely on post-transaction reviews, calculate risk scores in real-time.

Factors can include:

• Customer risk profile
• Transaction type and value
• Device and location signals
• Historical patterns
• KYC data.

A real-time score enables instant approvals for low-risk transactions while flagging suspicious ones for further checks.

Use Machine Learning and Analytics

Machine learning models are beneficial for real-time environments:

• They analyse large datasets quickly
• They adapt to new typologies and fraud tactics
• They reduce false positives through dynamic learning.

These models create a smarter and faster safety net when paired with human oversight.

Optimize Alerting and Case Management

In real-time systems, alert queues can quickly proliferate. Key strategies:

• Set clear thresholds to avoid overwhelming analysts
• Automate triage for simple alerts
• Link alerts to case management tools to speed reviews

Effective workflows keep investigations efficient and reduce customer friction.

Layer Monitoring with Other Controls

Transaction monitoring is one part of a defence strategy. Combine it with:

• Strong authentication (biometrics, multifactor authentication)
• Device fingerprinting to detect anomalies
• Behavioural analytics to spot unusual patterns

Multiple layers help detect sophisticated schemes without adding unnecessary delays.

Collaborate Across Functions

Real-time payment security is not just a compliance function. Fraud prevention, cybersecurity, and AML teams should work together. Sharing insights about new fraud schemes, mule account activity, and typology changes creates a 360-degree defense.

Governance and Continuous Testing

Instant payments require continuous monitoring and tuning.

• Run scenario testing to check false-positive rates
• Keep detailed documentation for every rule and model
• Version-control system changes for auditability
• Review thresholds regularly as payment volumes grow.

Governance ensures compliance while maintaining speed.

Prepare for Regulatory Expectations

Regulators are paying close attention to real-time payment risks. Expect focus on:

• How you identify and mitigate fraud typologies
• Your ability to investigate suspicious activity quickly
• Evidence of governance, testing, and documentation.

Strong monitoring systems demonstrate that your organization takes these risks seriously.

Balance Speed and Security

Instant payments thrive on trust. A frictionless experience is essential for customer adoption, but not at the cost of security. Real-time controls that minimize false positives while catching genuine threats create confidence for both customers and regulators.

Final Word

Real-time payments represent the future of financial services. They demand more intelligent, faster monitoring that blends technology, data, and human judgment. By using segmentation, pre-transaction scoring, machine learning, strong governance, and cross-functional collaboration, institutions can protect customers and deliver the seamless experience that instant payments promise.

Innovative financial institutions can keep pace with real-time demands while protecting against financial crime by investing in creative, adaptive transaction monitoring systems. At AML Right Source, we see this challenge as an opportunity to reimagine compliance for a faster world and to help our partners design controls that are as dynamic as the payment systems they safeguard.