Facial recognition is one of the biometric authentication forms that has changed cybersecurity and expanded hugely to users in the past years. Consumers now access online accounts, apps, or devices by scanning their faces easily and seamlessly. This cuts down wasted time in logging in and signing up while keeping security strong.
Face recognition is also widely spreading and wanted by users. A poll by the finance giant VISA found that over 86% of people prefer biometrics like facial recognition and voice recognition over passwords for identity checks or payments. Moreover, more than 131 million Americans use it daily for apps, accounts, or devices.
In this article, we cover face recognition technology for identity verification for all types of purposes including two factor authentication, how it works for verification, its benefits, comparisons to other methods and how to offer it to your users with no development.
Face recognition system verifies or identifies people using unique facial features, letting them access accounts and devices. During the authentication process, which can be two factor authentication for account protection, the system captures a new image of the user and compares it to the stored template. A successful match grants access or confirms identity, making the process both quick and precise.
Accuracy of face recognition in modern systems has improved dramatically, with top algorithms reaching over 99.5% reliability. This level of precision allows advanced systems to even distinguish between identical twins, something previously thought to be almost impossible.
Face recognition systems use cameras to capture images in either 2D or 3D, depending on the setup. They compare real-time data from photos or videos against stored records. Most implementations require internet connectivity since large databases are hosted on secure servers. The process involves advanced mathematical analysis, ensuring biometric matches without human error, and enabling seamless access to apps, services, systems, or even physical buildings.
The workflow of a face recognition feature typically consists of three main stages:
Facial recognition verifies identities with far greater accuracy than traditional credentials, considering the uniqueness of each human’s face characteristics. Unlike passwords or PINs that can be guessed, forgotten, or stolen, facial features remain unique and extremely hard to replicate.
Convenience is another key advantage. Users can unlock devices, authorize payments, or gain access to secure areas without needing to type passwords or carry physical keys. Once people experience the ease of using their face as a key, going back to older methods feels outdated and slow.
Compared to other biometric authentication ways, contactless operation adds a layer of hygiene and safety. Since there’s no need to touch fingerprint scanners, keypads, or doors, the spread of germs is minimized, something that proved especially valuable during the COVID-19 pandemic.
Facial recognition, when used for two factor authentication, instead of verifying identity of users (like in KYC for banking apps) takes a different approach compared to other two factor authentication methods like passwords, email verification, selfies, or even fingerprint scanning. This is how it briefly compares to each:
Businesses no longer need to build their own biometric systems from the ground up. Services like Authentica offer zero-coding biometric authentication, with the highest security standards and a pay-as-you-go model that minimizes initial costs.
Facial recognition is growing rapidly due to its security, convenience and speed. It is no doubt the best technology for identity verification, and for two factor authentication, it offers a very competitive choice in terms of security and convenience. One of its biggest downsides is that it needs complicated development, which can be resolved with a readily developed face recognition API as a service with no initial costs.
