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Consilient Bank Trials Demonstrate Federated Machine Learning Improves Effectiveness and Efficiency for Financial Crime Detection

Consilient Bank Trials Demonstrate Federated Machine Learning Improves Effectiveness and Efficiency for Financial Crime Detection

Consilient applies its federated learning model and machine-learning technology for anti-money laundering and countering the financing of terrorism efforts for financial institutions

In recent bank trials, fintech innovator Consilient demonstrated successful federated machine learning for the detection of financial crime. Traditionally, financial institutions silo their efforts to combat financial crime due to regulatory, privacy, technology, and competitive burdens. Consilient’s Dozer™ technology platform recently overcame these obstacles by using federated machine learning, a technique that trains algorithms to be shared across multiple financial institutions. Dozer leapfrogs the current systems for anti-money laundering and countering the financing of terrorism (AML/CFT) systems by sharing the algorithms and not the data. Dozer increased the effectiveness and efficiency in one study, reducing false positives from above 90% down to 12% while increasing the true positive discovery rate.

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For future phases of the Dozer rollout, Consilient entered into partnership with Intel to provide confidential computing through the use of Intel’s Software Guard Extensions (Intel® SGX) technology, which uses a hardware-based trusted execution environment to help isolate and protect data.

Consilient was publicly launched on October 29, 2020, by founder and CEO Gary M. Shiffman, Ph.D. (founder and CEO of Giant Oak and creator of GOST®), and Juan Zarate, global co-managing partner and chief strategy officer at K2 Integrity.

“We’re thrilled to see the first known instance of federated learning in the financial crime detection space. After training a machine-learning algorithm on a data set, moving it to a second data set, and then returning it to the first, Dozer demonstrated successful learning. The Consilient team, with our partner banks, proved that federated learning improved effectiveness and efficiency, all while preserving privacy,” said Shiffman, who is also the author of The Economics of Violence.

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“This revolutionary federated learning approach begins to solve the fundamental challenges we see in the current AML/CFT system, and when scaled, will form the basis for a new design for compliance risk management for financial institutions and regulators globally,” said Juan Zarate, who was the first-ever Assistant Secretary of the Treasury for Terrorist Financing and Financial Crimes, where he led the post-9/11 anti-money laundering and sanctions regime expansion in the United States and globally. “Financial institutions allocate large budgets for financial crime compliance and fraud detection. Consilient’s design provides a solution that helps decrease the cost and increases the efficiency needed to discover and manage real risk in their enterprises.”

“With increasing standards for both security and facilitation of the global financial regime, we now have a roadmap for the future of banking. We can improve the ability to fight criminal activity, preserve privacy and expand banking products to more communities,” added Shiffman.

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