Quantifind, an AI startup founded by two atomic physicists, secures $22M in funding to use data science to help automate financial crimes investigations

Quantifind, a Silicon Valley-based startup that provides AI solutions for anti-money laundering and fraud detection, today announced it has closed a $22 million funding to accelerate its pursuit of a growing market for automated financial crime and risk investigation.

Founded in 2008 by two atomic physics PhDs Ari Tuchman and John Stockton, Quantifind combines internal financial institution data with public domain data to offer a comprehensive and fully automated screen for external financial fraud and money laundering risk factors. For over a decade, Quantifind’s data analytics platform has been used by governments and Fortune 50 companies to gain insights from a comprehensive array of public sources.

The startup provides a single point of entry for all external data that might be relevant to a financial crime investigation. Using machine learning intelligence and data curation automation using its Graphyte platform, Quantifind is able to help investigators save 40% of their time and provide consistent reporting to regulators.

Quantifind’s success is rooted in its fusion of science with design; machine learning innovations with intuitive, feature-rich web applications and APIs. Today, its Graphyte platforms is used to combat financial crime risk. Its accuracy and features enable our customers to improve the efficiency of their AML investigations by 40% or more.

“In the face of exploding expenses in AML compliance, Quantifind leverages a decade of machine learning R&D to disrupt the investigative process with much-needed automation,” says Steve Krausz, General Partner of US Venture Partners and Quantifind board member.

With this strategic round, Quantifind will also expand the applications of its technology to financial health and intelligence investigations.

“Quantifind is a pioneer in extracting meaning from hidden signals found across disparate data sources,” added Marc Barrachin, Managing Director, New Product Development at S&P Global Market Intelligence. “Data on small- and medium-scale private companies can be minimal or unavailable, and the ability to identify meaningful leading indicators signaling a change in their financial health is critical to our customers. The Quantifind technology plays a vital role in extrapolating relevant signals for a large universe of companies.”

“Financial transaction analysis is critical to a range of national security applications, and Quantifind’s technology enables Intelligence Community analysts to perform this work efficiently and accurately at scale,” said A.J. Bertone, Partner at In-Q-Tel. “We are pleased to welcome Quantifind to our portfolio and look forward to providing government agencies the tools they need to make better financial crimes decisions, faster.

“We are fortunate to have the support of a consortium that can truly help Quantifind build upon our success in investigation automation,” said Ari Tuchman, CEO of Quantifind. “As we grow our AML/KYC practice, our team is excited to leverage synergies with S&P Global to offer similar solutions in the field of financial risk, and with In-Q-Tel to expand our footprint in predictive risk signal extraction for defense and intelligence applications.”