Deep Learning Revolutionizes Biometric Authentication

The new NIST face recognition vendor test necessitates the use of Biometrics as a Service (SaaS).


Deep learning and AI revolutionize biometric authentication

Every few years, the NIST conducts the Face Recognition Vendor Test (FRVT) to evaluate the performance of various biometric companies. Traditionally, established vendors like NEC and Cognitec lead the field. But, this year’s results indicate a massive change for the whole industry: Surprisingly, vendors that had been at the forefront for decades were surpassed by far concerning the accuracy of their biometric recognition. To be precise, the winning participants were 20 times (!) as good as the industry standard of the last NIST Face Recognition Vendor Test. A major reason for the significant progress is the advances in the field of artificial intelligence (AI) and deep learning, which revolutionizes biometric authentication.

A biometric authentication system bought 3 years ago, is completely outdated now

The test results imply a major consequence: A biometric authentication system bought 3 years ago, is completely outdated now – unless you had decided back then to use Biometrics as a Service in a SaaS model. With SaaS, vendors that constantly enhance their offers can easily let their customers be part of the innovations. Industry-changing developments like the FRVT’s results can dynamically be dealt with through auto-updates in a centralized server solution. Using Biometrics as a Service offers high scalability and cost efficiency for companies. From the customer’s point of view, a convenient and frictionless user experience is central. In a cloud-based solution, a single biometric face enrollment can be used for authentication across all devices. With the rapid developments happening right now in the biometrics industry, this is the way to keep your systems up-to-date and your customers satisfied.

Big Data, Deep Learning, and AI in Face Recognition

Innovations in deep learning technology are revolutionizing the way we think, the way we work, and the way we use data. For instance, the winners (e.g. Microsoft) take great advantage of the new possibilities generated through Big Data and AI. To train the algorithms for face verification, giant data sets of millions of faces were used. The important difference between traditional vendors and companies like Microsoft is the access to huge amounts of data. This opens unknown opportunities for training recognition engines. The ultimate result is an extreme discrepancy between the established vendors and new players. Deep convolutional neural networks for image classification are the key to generating new levels of accuracy in face recognition.

Biometrics as a Service in a SaaS model – automatically keeps up with the latest innovations

From the customers’ perspective, there is both good and bad news to report: On the one hand, the results have shown that biometric authentication, like any other industry, is subject to change depending on technological advancements. Massive changes in standards and processes can occur. On the other hand, there’s no need to keep away from biometric authentication software as it constantly evolves and gets better. This can be dealt with using Biometrics as a Service in a SaaS model. This way, companies can leverage the constant enhancement of the whole biometrics industry. By doing so, they can automatically keep up with the latest innovations and remain at the forefront.

Biometrics as a Service is the natural choice when it comes to deciding on a certain technology in a rapidly moving industry like ours.



Ann-Kathrin Schmitt
+49 911 9999 898 0