Our Federated solution

Play
Core AML/CFT model
Enhance transaction monitoring and customer due diligence
Correspondent Banking
Federated Learning model for enhanced risk management
High-Risk Typology models
Uncover hidden high-risk typology
High-Risk Jurisdictions model
Identifying high-risk transactions
In the news
Anti-money laundering (AML) risk management reimagined
The first Federated Machine Learning technology for AML and financial crime detection.
Federated learning shares suspicious behavioral patterns without ever moving data
Dramatically improves efficiency & effectiveness of AML controls
Reduces false positive alerts by
75%
300%
Improved identification of high-risk customers
Proactively pinpoint new and potential risks
Latest posts
February 28, 2025 | Blog
Visibility gaps in Correspondent Banking: why trad..
Financial institutions face an uncomfortable truth: despite investing billions in anti-money laundering contro..
READ MOREFebruary 20, 2025 | Blog
Solving Correspondent Banking compliance: Consilie..
Correspondent banking is essential for global trade and cross-border payments, but it comes with significant r..
READ MOREFebruary 18, 2025 | Blog
What banks did wrong in 2024: Critical AML failure..
Financial institutions paid more than $3.2 billion in AML-related fines last year. From major banks to emergin..
READ MORE