Production Sandbox Refine your rules with confidence, not guesswork
Cut false positives and expand risk coverage by optimizing your AML, screening, and fraud rules in a production-parity environment
Product Differentiators Optimize rules using dedicated sandbox tenant that mirrors your live production setup
Simulate recent customer behavior, tuning rules against your actual historical production data; no synthetic or stale lab data here
Test and deploy rules without the delay of vendor change requests and IT ticketing, through Hawk’s easy-to-use platform; eliminate consultant costs
Understand the true impact of changes before you make them, with complete configuration parity, unlike with traditional single-rule, sample and batch testing
Effortless rule simulation Enhance coverage while slashing false positives
Test and validate anti-money laundering, fraud, and screening rules before deployment:
- Click-of-a-button sandbox environment set-up, with the ability to duplicate settings
- User-friendly simulation set up and configuration
- Testing with live production data for accurate, timely decisions
- Integrated above-the-line (ATL) and below-the-line (BTL) testing to assess decisions
- Independent environment that eliminates disturbances to live risk detection
Sandbox testing process Easily configure rules and parameters for straightforward, accurate and hands-on testing
1. Set up sandbox environment
Select which tenant to replicate and, with the click-of-a-button, automatically port over user access, roles, and existing rule sets
2. Adjust rules
Create new rules, deactivate existing rules, and modify dynamic rule filters and parameters, all with the same rule builder and UI as your production environment
3. Select testing parameters
Choose a subset of transactions to simulate rule changes on by selecting your desired sample size, timeframe, and relevant alert status(es)
4. Run the simulation
Know when your results will be ready thanks to the simulation time estimate
5. Assess the outcomes
Easily toggle between sandbox and production mode; once you’re confident with your changes, adjust your live production rule settings to match
THE HAWK DIFFERENCE Discover how Hawk raises the bar for rule testing
The Traditional Way
- Synthetic or stale lab data that fails to capture your financial institution’s real-world money laundering and fraud risk
- Heavy reliance on vendor change requests and IT ticketing, delaying response and rule deployment
- High consultant costs for rule tuning and evaluation
- Frequent rule-changing breaks due to software version mismatches between test and production
The Hawk Way
- Your own fresh, production-grade data in a live sandbox for more accurate tuning
- Self-serve rule management and testing that accelerates your response to risk
- Rule simulation that's simple and user-friendly, enabling you to optimize rules without IT or vendor support
- Simulation environment that runs the exact same software as production so changes don't break with deployment
Improve Your Anti-Financial Crime Program Outcomes Effortlessly improve rule performance across your whole program
AML Transaction Monitoring
Expand risk coverage and cut false positives by tuning monitoring rules and thresholds against your actual transaction history; ensure only the changes you've validated are pushed to production
Fraud Prevention
Stop flash fraud without creating unnecessary customer friction by deploying rules quickly, then tuning and testing thresholds and parameter adjustments in the production sandbox
Payment Screening
Reduce false hits on legitimate payments while maintaining sanctions coverage by testing fuzzy-matching configurations and screening logic
Articles & Resources The latest from Hawk
Financial crime experts from ING, Wintrust, and Grant Thornton joined Hawk to share their experiences of building defensible, operationally embedded, and regulator-ready AI models.
AML thresholds are a cornerstone of risk-based approaches but come with several challenges. They are often a significant source of false positive alerts due to their generic nature. However, raising all thresholds to reduce false positives and missing genuine financial crime risk is not an acceptable trade-off either. We explore how AI can help.
AI offers a new approach to AML risk detection. In this article, we discuss how AI improves on rules-based AML technology.
Request a demo Stop 2X more threats with 50% less effort with Hawk
Request a demo with one of our product experts and find out if Hawk meets your business needs.
During the demo process you'll touch on Hawk's:
- API infrastructure and data integration capabilities
- Modular design and flexible multi-tenant set up
- No-code rule builder, AI feature library, and model explanations
- Any further questions you may have