Quantexa raises $129M at a $1.8B valuation to help navigate online fraud and customer data management

Financial fraud and other online crime continue to present major threats to businesses, and they remain a key focus for regulators requiring more rigorous efforts to keep illicit activity at bay. Now, London-based Quantexa — one of the big startups providing AI and other tools to major banks and others in financial services, governments and other major organizations to tackle these challenges — is announcing $129 million in funding, a round that underscores how services like these are being viewed in the market today, and Quantexa’s specific traction within it.

The funding is coming in the form of a Series E that values the startup at $1.8 billion. For some context, this is a major step up from its previous round nearly two years ago (in July 2021), a Series D of $153 million that was raised at an $800 million – $900 million valuation. (It’s also a higher number than some thought the round would be: last week a report of Quantexa raising estimated that it would be “close to $1.5 billion”.) 

Singapore’s sovereign wealth fund GIC — which was also a major investor in Stripe’s recent $6.5 billion round — led this round, with participation from previous backers Warburg Pincus, Dawn Capital, British Patient Capital, Evolution Equity Partners, HSBC, BNY Mellon, ABN AMRO and AlbionVC. Prior to this round, Quantexa had raised $240 million.

The last six months have been such a tricky time for a lot of startups looking to raise money, but Quantexa is one of the small group that has bucked that trend.

CEO and founder Vishal Marria said in an interview that the round was oversubscribed and is coming at a time when the startup still has “between two and three years of runway” from previous rounds and cash it’s generating from its business.

Part of the reason for the strong interest from investors is because of how the company has been doing.

The company’s core products are in the area of risk and compliance — for example tools to help verify user identities, detect money laundering and to carry out financial investigations. Alongside that Quantexa is using some of the same techniques to build out bigger user “graphs” for business intelligence and CRM purposes.

Together these are used by hundreds of customers in some 70 countries, the company said, including major enterprise organizations like BNY Mellon, HSBC, Standard Chartered, Danske Bank, Vodafone and the Public Sector Fraud Authority within the U.K.’s Cabinet Office. Marria said that Quantexa has doubled its business in the last 18 months: “We’ve doubled the number of users, the revenues and the number of industries we target,” he said.

Interestingly, Quantexa’s fundraise comes in on the same day that another KYC startup, Fourthline, also announced a big round of $54 million. Fourthline’s approach up to now (and going forward) has been to build everything it uses from the ground up. Quantexa is taking a different view: it builds but also leans heavily on APIs to work with whatever its customers might already have integrated into their platforms and operations.

What the two have in common is a fundamental view of how to use AI tools in tackling the issues of fraud, identity management and compliance: The techniques used by bad actors are sophisticated and too numerous for humans on their own to track, so machine learning, natural language, computer vision and other AI technology can be built to help in that task.

Quantexa’s plan is to double down on that strategy: The plan will be to use the fresh funding, plus the money that the company already had in its coffers, to invest in building out new technology, but also to make acquisitions to grow inorganically. Given the number of interesting enterprise and big data startups that have emerged over the last several years, and the number that have found it hard to raise money and scale, there are a number of interesting targets.

Marria noted that a recent acquisition, of the Irish startup Aylien, points to the kinds of acquisitions Quantexa might make: Aylien’s specialty was natural language processing (NLP) and advanced AI and working with unstructured data, he said.

Notably, Quantexa is not yet profitable, but Marria said investors are willing to be patient because the startup’s been hitting so many of its other targets. “That gives the community confidence that our plan is accurate and we can deliver on it.” The company is growing ARR at 140% (at Series D subscriptions revenues were 108%), and he projects that the company will make $100 million in revenues next year, turning profitable by 2025.