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Federated Learning Models for AML/CFT
Our Federated Models
Introducing federated learning models for anti-money laundering (AML).
Consilient models are crafted to significantly enhance efficiency and effectiveness in identifying risks through the exchange of behavioral patterns and insights, all while preserving data privacy.
Designed to address the challenges with core AML processes, federated learning introduces industry collaboration to fight financial crime.
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..
READ MOREJune 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 ..
READ MOREMay 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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