Consilient Announces $3 Million Seed Funding Round for the Development of Next-Generation Financial Crime Compliance Technology
Investment in leadership and technology innovation positions the company to redefine anti-money laundering and combating financial fraud
WASHINGTON, May 24, 2022 /PRNewswire/ — Consilient, a fintech innovator aiming to transform financial crime compliance, today announced it has secured a private $3 million seed funding round that will help the company’s vision to become the leader in the development of next-generation machine learning technology to detect and prevent illicit activity within financial ecosystems. Consilient was founded through a partnership between K2 Integrity and Giant Oak.
The seed round will provide working and growth capital to accelerate client pilots, make further investment to speed up the rapid build program expanding product design and deployment capabilities, as well as augmenting the existing teams. Consilient’s federated machine learning technology enables organizations to discover and manage financial crime risks dynamically and effectively, while preserving privacy. It enables enterprises to gain insights across the industry without sharing or moving data.
“Criminals adapted during the pandemic and continue to evolve. But recent innovations in technology can empower those individuals and teams engaged in combatting financial crime,” said Gary Shiffman, CEO and co-founder of Consilient. “Current detection and prevention systems simply do not work, in spite of massive investments made each year. As an industry, it is critical that we implement the next generation anti-money laundering solution. It is our goal to solve this fundamental challenge.”
“Consilient is poised to reshape the way the financial system prevents financial crime,” said Juan Zarate, chairman and co-founder of Consilient. “Consilient elegantly solves at once the bedeviling problems affecting the AML/CFT system globally: inefficiency, ineffectiveness, concerns for data privacy and security, and the decentralization of the financial system. To manage financial crime risk and sanctions exposure in the 21st century, Consilient will need to be a fundamental part of the solution for banks, payment providers, the crypto industry, and regulators.”
Consilient has two technology patents pending for an adaptive transaction processing system and the orchestration techniques for adaptive transaction processing. The company also expanded its senior leadership team with the appointment of Laurence Hamilton as chief commercial officer and Christina Schott as head of customer success. Hamilton and Schott follow the hire of Shawn Holtzclaw as Consilient’s president & chief legal officer.
Hamilton joined Consilient after helping launch a UK-based digital bank, JN Bank UK, as its chief commercial officer. He has spent over two decades leading international data and analytics companies, developing international market strategies and new product development for credit, fraud and anti-money laundering solutions. Schott joined Consilient from BMO Harris Bank, where she served as manager of fraud operations strategy and was responsible for the department’s transformation. She brings over 18 years of technology experience, implementing flexible, scalable solutions for fraud, identity and authentication risk mitigation with a focus on the customer experience.
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 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.