Incognia rides steady growth as it aims for half a billion users

Having accrued impressive financial support from a $15.5 million series A funding round in mid-2022, followed by $31 million in series B funding from Bessemer Venture Partners this past January, Incognia is cementing a niche for itself in identity verification using a unique combination of mobile location authentication and device fingerprinting. Without collecting personal information beyond a user’s home address, Incognia’s location identity system analyzes behavioral analytics in the form of device location tracking to determine the likelihood that transactions are legitimate.

Incognia has been leaning toward location authentication for several years, and in an interview with Biometric Update, Incognia CEO André Ferraz says the company has grown quickly in that time, gaining customers in the U.S., Latin America and Asia. In July, the company secured its first European customer in FreeNow, a multi-mobility app centered on taxis, bringing its footprint to nearly 190 countries worldwide.

Location identity model flourishes in immediacy of gig economy

“Our sweet spot from a global standpoint has been gig economy marketplaces,” says Ferraz. “We’re seeing that these apps in, for instance, food delivery and ride hailing are some of the most complex types of applications when it comes to fraud prevention.” In gig economy scenarios, the variety of stakeholders involved in any given transaction and the addition of factors like time increase complexity and necessitate new kinds of authentication and fraud detection.

“For example, in food delivery, you have to deliver your orders immediately, right? So if there is something suspicious, you can’t afford to pause that transaction, take a deeper look, then decide what you’re going to do. You have to decide everything in real time.”

Ferraz notes that Incognia’s location-based analysis is “not a complete replacement for the identity verification process, but a strong complement.” By bringing identity verification, device recognition and behavioral analytics together, secure fraud prevention can be layered without adding additional friction to the customer experience. “The only thing they need to do,” says Ferraz, “is authorize that the app is going to collect location data for this verification process.”

Logins from trusted locations – for example, places the device’s user often goes, like home or the office – can be processed with almost zero friction. On the other hand, “if we identify that there is a mismatch – for example, someone is trying to access your account and we’re recognizing a different divide at a completely new and different location – then we’re going to flag it as high-risk.”

AI not a major factor in Incognia’s location data approach

Ferraz points out that Incognia’s model is also relatively immune to AI hype. “A lot of companies have been discussing how AI can help fraud prevention companies and fraud prevention solutions. But the new advancements in AI are not really that helpful for companies like us.”

Most companies in the biometrics and identity verification space, he notes, have been using machine learning and collecting data for a while. “But the reality is that generative AI has been a lot more helpful to the fraudster.” Phishing is easier than ever and liveness detection is in a dead heat with deepfake technology that is evolving by the hour.

Ferraz says that by taking the focus off voice or face biometrics and drilling down on how and where users move with their authenticated devices, Incognia’s ID product has created pressure on competitors battling bots and deepfakes, and supercharged the company’s growth, tripling revenue since the series A round.

In the near future, Incognia hopes to focus on expanding its network, to maximize the amount of customer data that can be applied across its client base. Ferraz says that “for every new customer that joins this platform, all of the existing customers directly from the data that this new customer is providing.” One of Incognia’s main goals for the year is to cross the half billion user mark – which should be achievable, given that it already has more than 400 million.

Ferraz also teases the launch of some “very, very big product features by the end of the year.” As such, in keeping with Incognia’s location behavior-based model, it would be wise to pay attention to where the company’s current growth spurt will take it.

Article Topics

behavioral biometrics  |  biometrics  |  digital identity  |  fraud prevention  |  identity verification  |  Incognia  |  location authentication