Product profile
AML Transaction Monitoring
By Hawk
A transaction-monitoring solution that combines configurable rules, anomaly detection, explainable AI, alert workflows, and audit trails for AML investigations.
Product research reviewed
Research notes
What the public record shows
- Overview
- A transaction-monitoring solution that combines configurable rules, anomaly detection, explainable AI, alert workflows, and audit trails for AML investigations.
- Hawk profile context
- Hawk provides fraud and anti-money-laundering technology for regulated financial organizations. Its transaction-monitoring solution combines configurable rules with AI-based detection and investigation workflows.
- Primary use cases
- Monitoring client and transaction activity for known and emerging money-laundering typologies and managing resulting investigations.
- Target customers
- Banks, payment firms, and fintechs.
- Data coverage
- Not publicly disclosed
- Deployment
- Not publicly disclosed
- Integrations
- Not publicly disclosed
- Implementation
- Not publicly disclosed
- Pricing approach
- Not publicly disclosed
- Documented strengths
- Not publicly disclosed
- Limitations and considerations
- Not publicly disclosed
Evidence matrix
Capabilities
The table covers every canonical capability in the product's listed categories.Unverified means the reviewed public sources did not confirm the capability; it does not mean the capability is absent. “Not supported” is used only for a directly sourced, explicit limitation.
| Category | Capability | Evidence state | Source note |
|---|---|---|---|
| AML Transaction Monitoring | Prebuilt scenario libraryShips with detection scenarios covering common typologies. | Unverified | No supporting public documentation was identified in the reviewed sources. |
| AML Transaction Monitoring | Custom rule authoringCompliance teams can author and modify detection logic without vendor engagement. | Supported | The product page documents self-service rule configuration, flexible templates, and production sandbox testing.Official evidence ↗ |
| AML Transaction Monitoring | Machine-learning detectionUses ML models alongside or instead of rules. | Supported | The product page describes AI anomaly detection and multiple detection layers for known and unknown threats.Official evidence ↗ |
| AML Transaction Monitoring | Tuning & backtestingSupports scenario tuning, simulation, or backtesting against historical data. | Unverified | No supporting public documentation was identified in the reviewed sources. |
| AML Transaction Monitoring | Real-time monitoringCan evaluate activity in real time, not only in batch. | Supported | The product page states that all transactions receive AI assessment and describes real-time AI results.Official evidence ↗ |
| AML Transaction Monitoring | Alert explainabilityAlerts show the contributing factors in terms an investigator and auditor can follow. | Supported | The product page documents AI explanations intended to improve investigator speed and clarity.Official evidence ↗ |