Would you be surprised to learn that over 95% of anti-money laundering alerts are false positives? It’s true, and with the pressure of regulators’ mandates and thinning resources, compliance teams are already under tremendous stress to maintain the integrity of their organizations and the broader financial system. Rooting out false positives can help—but how can this be done?

Federated learning can help fight financial crime in a more meaningful and accurate way. What is federated learning? It is the principle behind Consilient’s technology: a behavioral-based, ML-driven governance model that allows its algorithm to access and interrogate data sets in different institutions, databases, and even jurisdictions without ever moving the data.

This model moves beyond traditional rules-based monitoring and toward one that facilitates information sharing among various authorities and institutions across the globe; enables collective learning on complex threats; distributes and shares risk; and simultaneously safeguards customer privacy and data.

Interested in learning more? Download Consilient’s white paper, authored in partnership with Intel, to get up to speed and take a deep dive into how this technology can help enhance and maintain financial crimes compliance programs now and in the future.