Reduce false positives & increase workflow efficiencies with AI-powered Smart Alerts
Rules library of AML/CFT industry typologiesNo-code self-serve rules builderSimplified view of team performanceAlert prioritization to boost efficiencyScalability to billions of transactions
Reduce false positives by 70%
Our solution learns from your analysts and data.
Allows you to prioritize and focus on the greatest risks to your business.
Use your own rules and benefit from AI
Create your own transaction monitoring solution by choosing from our library of red flags and suspicious activity scenarios. Set thresholds based on your risk exposure.
Where rules are unable to detect specific activity, our AI capability fills the gap to precision.
Reduced false positives by up to 70%
Saved 80% of time spent on building risk scenarios
Monitored billions of transactions at 100 TPS with sub second response time
Went live within 2 weeks
TransferMate is one of the world’s leading B2B payments infrastructure-as-a-service companies. Based in Ireland, the company enables individuals and businesses to make seamless, cost-effective cross-border payments in more than 201 countries and 141 currencies.
Lumon has provided overseas payments and foreign exchange services to private individuals, small-to-medium enterprises (SMEs), and larger corporates for over two decades.
HTB is working to stay ahead of the rapidly evolving financial crime landscape, and the growing sophistication of fraudsters. To support this work it was looking for a transaction monitoring and screening solution that would meet the needs of its growing customer base while safeguarding the bank’s reputation.
What is AML Transaction Monitoring?
How to Set AML Transaction Monitoring Thresholds
How To Reduce False Positives In Machine Learning
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