Facial recognition: Definition, how it works and business use cases
Facial recognition has become a standard technology in identity verification and biometric solutions.
More and more companies are integrating this technology into their registration, onboarding and access control processes to strengthen security and reduce the risk of fraud.
But how does facial recognition actually work? Is it reliable? And when should it be used?
In this article, we explain everything you need to know about facial recognition and its role in identity verification.
What is facial recognition?
Facial recognition is a biometric technology used to identify or verify a person’s identity based on their face.
It works by analysing unique facial characteristics, such as the distance between the eyes, the shape of the nose and facial contours, to compare one image with another.
Why use facial recognition?
As services become increasingly digital, companies need to verify users’ identities remotely, without any physical interaction.
Facial recognition addresses several key challenges.
Prevent identity fraud
Identity fraud, including identity theft and impersonation, is becoming increasingly common.
Facial recognition can be used to verify that the person presenting an identity document is indeed its legitimate holder.
Secure remote identity verification
In a digital environment, there is no face-to-face interaction.
Facial recognition can therefore provide a level of security comparable to an in-person identity check.
Automate identity checks
Biometric technologies make it possible to automate identity checks, resulting in:
- fewer human errors
- faster processing
- improved traceability
How does facial recognition work?
Facial recognition is typically integrated into a multi-step identity verification process.
1. Facial capture
The user takes a selfie or a short video using their smartphone or computer.
2. Biometric analysis
The system analyses facial characteristics to create a unique biometric template.
This template is a mathematical representation of the face that can be used for comparison.
3. Face matching
The captured face is compared with a reference image, typically the photo on an identity document.
This step verifies that the person matches the identity they claim to have.
4. Liveness detection
To prevent fraud, including attempts involving deepfakes, an additional security step is often included.
Liveness detection verifies that the person is real and physically present at the time of the check.
Is facial recognition reliable?
Facial recognition is considered a reliable technology when used within a well-structured verification process.
Its accuracy depends on several factors, including:
- image quality
- the algorithms used
- the use of liveness detection
- its combination with other checks, such as document authenticity verification, data extraction (OCR), and barcode and MRZ reading and validation
When used on its own, facial recognition can have limitations. However, when combined with other identity verification technologies, it can provide a high level of security.
Best practices for using facial recognition
For effective use:
✔ Combine facial recognition with other verification technologies
✔ Integrate liveness detection
✔ Automate identity checks
✔ Keep a record of the checks performed
✔ Comply with applicable regulatory requirements*
*As facial recognition involves biometric data, its use is regulated by the GDPR and requires, among other things, user consent.
Facial recognition is now a key component of modern identity verification solutions. When used appropriately, it helps secure processes while providing a smooth user experience.
Looking to integrate facial recognition into your processes?
Discover how CheckHub helps you automate identity verification with facial recognition, secure your onboarding processes and reduce identity fraud.