Tag: Federated Learning

AML compliance teams are facing growing challenges in how they handle backlogs of alerts. Traditionally, banks and financial institutions have approached these backlogs by...

Feedzai has unveiled Feedzai IQ, a new suite of solutions designed to help financial institutions detect and prevent fraud using shared intelligence—without compromising customer...

Ripping out and replacing anti-money laundering (AML) systems is no longer a practical option for most financial institutions. According to Consilient, deeply embedded legacy...

Customer Risk Ratings (CRRs) have long been integral to anti-money laundering and counter-terrorist financing (AML/CFT) frameworks. According to Consilient, despite their importance, many financial institutions...

As 2025 unfolds, financial institutions face an evolving array of challenges. The recent Executive Perspectives on Top Risks Study conducted by Protiviti and NC State University, which garnered insights from over 1,200 board members and executives, sheds light on the primary concerns encompassing financial crime compliance, AI integration, and increasing regulatory oversight.

Money laundering activities in the United States alone are estimated to total $300bn annually. In 2023, penalties for anti-money laundering (AML) violations in the U.S. exceeded $5bn—a 69% rise from the previous year. These figures underline the urgent need for a more effective approach to combatting financial crime.

Federated learning is a ML technique that enables multiple entities to train a model together while keeping their data decentralized.

The global financial landscape is increasingly plagued by the complexities of financial crime compliance. As the severity of global money laundering grows, major financial...

Consilient, which is on a mission to transform how businesses address financial crime, has launched its financial crime detection and prevention solution to market.