Our Federated solution

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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

June 17, 2025 | Blog

Smarter AML triage: How ranked scoring boosts risk..

The volume problem isn’t going away. But how you triage it can change. By the end of 2024, financial institu..

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June 12, 2025 | Blog

Backlog = hidden risk: A ranking-based approach to..

In many banks, aged alerts are reviewed in the order they were created, not based on the severity of the risk ..

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May 13, 2025 | Blog

Don’t rip and replace: How modern AML models can..

There’s a reason financial institutions push back on full-scale AML overhauls: they’re expensive, complex,..

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