Incognia received impressive financial backing from a $15.5 million Series A funding round in mid-2022, followed by a $31 million Series B funding round from Bessemer Venture Partners last January. The company is now establishing itself in a niche in biometric identity verification with 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 biometrics in the form of device location tracking to determine the likelihood that transactions are legitimate.

Incognia has been using location authentication for several years. In an interview with Biometric Update, Incognia CEO André Ferraz said the company has grown rapidly during this time, gaining customers in the US, Latin America and Asia. In July, the company won its first European customer with FreeNow, a multi-mobility app for taxis, giving it a presence in almost 190 countries worldwide.

Location identity model flourishes in the immediate gig economy

“Our strength from a global perspective is gig economy marketplaces,” says Ferraz. “We see that these apps, such as food delivery and ride-hailing apps, are among the most complex types of applications when it comes to fraud prevention.” In gig economy scenarios, the multitude of parties involved in a transaction and additional factors such as time increase the complexity and require new types of authentication and fraud detection.

“In food delivery, for example, you have to deliver your orders immediately, right? So if something suspicious comes up, you can’t afford to pause the transaction, take a closer look and then decide what you’re going to do. You have to decide everything in real time.”

Ferraz points out that Incognia’s location-based biometrics “are not a complete replacement for the identity verification process, but a strong complement.” By combining identity verification, device recognition and behavioral biometrics, secure fraud prevention can be achieved without adding friction to the customer experience. “All they have to do is authorize,” says Ferraz, “for the app to collect location data for this verification process.”

Logins from trusted locations – for example, places where the device user frequently goes, like home or the office – can be handled with almost no friction. “However, if we see there’s a mismatch – for example, if someone tries to access your account and we see another disconnect in a completely new and different location – we flag that as high risk.”

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

Ferraz points out that Incognia’s model is also relatively immune to the AI ​​hype. “Many companies are discussing how AI can help companies and fraud prevention solutions. But the new advances in AI are not really 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 some time. “But the reality is that generative AI is much more helpful to fraudsters.” Phishing is easier than ever, and authenticity detection is neck and neck with deepfake technology that is evolving by the hour.

Ferraz says that by shifting the focus from voice or facial biometrics to a deeper study of how and where users move with their authenticated devices, Incognia’s ID product has put pressure on competitors in the fight against bots and deepfakes and accelerated the company’s growth, with revenue tripling since the Series A funding round.

In the near future, Incognia wants to focus on expanding its network to maximize the amount of customer data that can be applied to its entire customer base. Ferraz says, “With every new customer that joins this platform, all existing customers will directly benefit from the data that this new customer provides.” One of Incognia’s main goals for this year is to surpass the half-billion user mark – which should be achievable, given that the company already has more than 400 million users.

Ferraz also announces the launch of some “very, very big product features by the end of the year.” So, given Incognia’s location-based behavior model, it would be wise to keep an eye on where the current growth spurt will take the company.

Article topics

Behavioral biometrics | Biometrics | Digital identity | Fraud prevention | Identity verification | Incognia | Location authentication