Consilient Brings to Market its Next-Generation Federated Learning Solution for Financial Crime Detection
Solution transforms risk management by securely detecting high-risk entities and behaviors across different financial institutions while preserving data privacy
WASHINGTON — February 28, 2023 — Consilient, a fintech innovator transforming the way the world addresses financial crime, today announced the next generation of the Consilient Federated Learning (FL) solution. Consilient is the first-ever FL solution for financial crime detection and prevention. The Consilient Platform and its FL models enable banks and other financial institutions to detect high-risk entities and behaviors by sharing insights across different data environments and organizations. With Consilient, algorithms travel and insights are shared, but data never leaves its environment.
For financial institutions and similarly regulated entities, sharing data across organizations or even borders is typically not possible due to privacy regulation and data controls, but Consilient enhances both dynamic analytic insights and data privacy by moving the analytics to the data and deploying privacy-enhancing technology, rather than moving and sharing the data itself. As a result, financial institutions, payment platforms and providers, and regulators can increase the efficiency and effectiveness of existing financial crime controls while discovering previously unseen risks and behaviors.
Preventing financial crime and protecting the integrity of the financial system is a global imperative. Money laundering typically costs the global economy $800 billion-$2 trillion annually and is used to fund illicit activities such as human trafficking, the global drug trade, terrorism, organized crime, and other nefarious activities. Consilient is designed to enable financial institutions to increase the rate at which they can detect financial criminal and money laundering activity substantially, while reducing the resources required to do so.
With the use of FL, an extension of machine learning, Consilient trains models in dispersed data sets and then travels those models between organizations, enabling “insight sharing” across banking and financial institutions. It can also be used within organizations to share insights where data is not able to be moved or shared. For regulators, supervisors and financial intelligence units, this approach enhances oversight, enables gathering and testing of strategic intelligence, and advances of proactive supervision of regulated sectors and channels.
The Consilient Platform’s “High Risk Entity” model uses bank transaction data to create features that are equivalent to high-risk behaviors. The system flags anomalous activity beyond the bounds of expected behavior, indicating transactions and financial activity that require further investigation. Consilient’s Model Library currently consists of 18 different Consilient models that can be used to identify high-risk and suspicious behaviors tied to money laundering and financial crime.
“Despite significant efforts by banks to detect criminals in their systems, they are inherently limited in their overall effectiveness because of the inability to share insights across institutions, limitations of legacy systems, volumes of ‘noise’ created by inefficient systems, and regulations,” said Gary Shiffman, CEO and co-founder of Consilient. “Consilient is the first company to introduce FL for the detection of financial crime and it is our mission for global organizations to use FL to transform how the world prevents financial crime.”
“With the maturation of the Consilient models and product, we are ushering in a new paradigm of financial crime risk management that dynamically discovers risk while enhancing data privacy,” said Juan Zarate, Chairman and co-founder of Consilient. “Consilient enables collaboration to prevent financial crime more effectively and efficiently at time when global regulatory expectations are increasing.”
In May Consilient announced that it secured a private $3 million seed funding round that helped the company with the development of next-generation federated learning technology to detect and prevent economic crime. Today’s announcement is the next phase in that development – the general availability of a solution for financial crime. Consilient was founded through a partnership between K2 Integrity and Giant Oak. Learn more about Consilient here.
Founded through a partnership between K2 Integrity (www.k2integrity.com) and Giant Oak (www.giantoak.com), Consilient is the 21st century answer for best-in-class anti-money laundering and countering the financing of terrorism (AML/CFT) compliance solutions. Consilient’s mission is to transform the prevention of financial crime. Consilient’s solution is a behavioral-based, machine learning-driven utility and governance model design that enables financial institutions to more effectively share information about risks and illicit actors in real time, while adhering to privacy protections and data localization restrictions. Consilient uses federated learning, which allows financial institutions to access and interrogate data sets in different institutions, databases, and even jurisdictions to discover previously unknown but existing risks.