AML Transaction Monitoring

AI precision to catch more risk with less noise

Enhance risk detection with Hawk’s AML Transaction Monitoring solution. Fuse rules with AI for efficient, effective alerts, minimizing false positives. Optimize your risk management to suit your organization.

Product Differentiators

Manage your AML risks effectively, without adding complexity

• Flexible, user-friendly rule set up
• Real-time AI innovation & results
• 360 degree, unified view of risk

transaction monitoring software

Comply with confidence

Hone in on actual money laundering activity without compromising on compliance. Hawk empowers teams with:

• Coverage of money laundering typologies, like structuring, layering and smurfing
• Monitoring of all client, product and transaction types
• Multiple layers of detection to defend against known and unknown threats, refined by AI
• Multi-tenancy to set global controls and meet regional requirements
• Pre-built investigative workflows and customer-centric investigations
• 4-eye review and model approval processes
• Automated audit trails and integrated SAR / CTR filing

AML detection

Protect against illicit actors with multiple layers of defense

Protect against foundational threats

• Build rules tailored to your risk profile and refine, with flexible rule templates & self-serve functionality

Increase coverage

• Detect outliers & new criminal patterns. Hawk's anomaly detection builds context, assessing whether activity is truly suspicious or just a one-off before flagging for review

Cut through the noise

• Reduce overall false positives, with AI that identifies common root causes for false alerts and informs triage of similar cases

Optimize over time

• Gain control and improve detection accuracy with streamlined tools for model tuning and AI retraining on production data

The Hawk Difference

Discover how Hawk raises the bar for transaction monitoring

The Traditional Way

• One-size-fits-all approach that doesn’t reflect local regulations
• Rules-only detection that finds more false positives than true threats
• Manual, vendor or excel-driven rule tuning on stale data
• AI that just filters already inaccurate results
• Fragmented view of a customer's risks
• Outdated user interface requiring many clicks and flipping back and forth between systems

The Hawk Way

• Multi-tenant infrastructure that supports regional regulations
• Multiple layers of defense reinforced with AI precision
• Self-serve model configuration and production data sandbox testing
• Full AI assessment of all transactions with AI explanations that drive speed and clarity
• Unified risk profile highlighting customer activities and risks flagged
• Streamlined investigations with available risk data all in one place

Awards & Recognition

Leading the industry forward

Agentic AI: A Practical Guide for Anti-Financial Crime and Compliance Leaders

How is agentic AI changing the way that financial crime and compliance teams work? Our latest whitepaper provides you with 50 pages of insight on the best use cases for agentic AI, covering:

• Improving investigations
• Enhancing system accuracy
• Optimizing workflows

Frequently Asked Questions

Want to know more?

What is AML transaction monitoring?

AML (Anti-Money Laundering) transaction monitoring is the continuous process of overseeing a customer’s financial activity in real-time or on a batch basis. It involves analyzing historical and current data—such as transfers, deposits, and withdrawals—to identify patterns that suggest money laundering, terrorist financing, or other financial crimes. Unlike one-time identity verification, transaction monitoring is an ongoing protective measure.

Why is transaction monitoring mandatory for financial institutions?

Transaction monitoring is a core regulatory requirement under global standards like the Bank Secrecy Act (BSA) and the EU’s Anti-Money Laundering Directives. Beyond legal compliance, it is essential for:

• Risk Mitigation
• Reporting Obligations
• Preventing Financial Crime

What types of behavior get flagged in AML monitoring?

The goal of transaction monitoring tools is to detect "red flags" or anomalies. Common patterns include:

• Structuring (Smurfing)
• Rapid Movement of Funds
• Atypical Activity
• High-Risk Jurisdictions

How does AI improve the monitoring process?

Legacy systems rely on rigid "if-then" rules that often trigger a high volume of false positives (legitimate transactions flagged as suspicious). AI-driven transaction monitoring software uses machine learning to:

1. Understand Context
2. Reduce Noise
3. Identify New Patterns

How does transaction monitoring align with global AML regulations?

Effective AML monitoring is the cornerstone of regulatory compliance. It ensures that financial institutions meet stringent requirements set by international bodies.

What are AML typologies, and why does coverage matter?

In the world of financial crime, "typologies" are the established patterns and methods criminals use to disguise illicit funds. Comprehensive typology coverage is critical because if your transaction monitoring system only looks for simple, single-event triggers, it will miss complex, multi-stage schemes used by modern criminal networks.

Money laundering typologies include:

• Structuring and Smurfing
• Layering & Circular Flows
• Mule Activity & Network Detection
• Trade-Based Money Laundering (TBML)
• Crypto-Asset Obfuscation