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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
January 20, 2026 | Blog
The future of AML effectiveness: The metrics regul..
Coverage, precision, prioritization, and case aging reveal an AML program’s true operational behavior un..
READ MOREJanuary 15, 2026 | Blog
Introduction to Crypto AML compliance and DeFi act..
More than $2 billion in crypto was stolen in 2025, with stablecoins accounting for over 60% of identified illi..
READ MOREJanuary 15, 2026 | Blog
pKYC vs. periodic reviews: The future of Enhanced ..
Banks don’t fail at KYC because they lack data. They fail because customer risk stops learning once onboardi..
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