What is Liveness Detection and Face Matching?

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Liveness detection vs face matching

In the realm of digital onboarding, two important technologies have emerged to enhance security and verify the identity of individuals: Liveness Detection and Face Matching. These technologies play a crucial role in ensuring the authenticity and accuracy of the digital onboarding process. 

At QuickSign, we are determined to make life simpler. Scroll to demystify what lies behind Liveness Detection and Face Matching:

Liveness Detection:

Liveness Detection is a technology designed to distinguish between a live person and a fraudulent attempt using a static image (a stolen image on Facebook for example) or video playback. It adds an extra layer of security by detecting and preventing spoofing attacks during the onboarding process (beware deep fakes!). Liveness Detection algorithms analyze various facial movements and characteristics, such as blinking, head rotation, and facial expressions, to confirm the presence of a live person.

By leveraging advanced computer vision and machine learning techniques, Liveness Detection algorithms can effectively detect and identify signs of life that cannot be replicated by static images or prerecorded videos. As a result, this technology significantly reduces the risk of impersonation fraud. Consequently, it ensures that only legitimate individuals can successfully complete the digital onboarding process, thus bolstering the security and trustworthiness of the system.

Face Matching:

Face Matching, also known as Face Recognition or Facial Biometrics, is a technology that compares and matches a person’s facial features against a reference image or a database of known identities. It analyzes key facial landmarks and unique characteristics to create a biometric template. The system then compares the captured image with existing templates for identification or verification purposes.

During the digital onboarding process, Face Matching algorithms compare the live image or video of the individual’s face with their reference image or identity document photo to establish a match. This technology ensures that the person initiating the onboarding process is the rightful owner of the provided identity document. As a result, it effectively reduces the risk of identity theft and fraud.

Combined Benefits:

The combination of Liveness Detection and Face Matching technologies provides a robust solution for secure digital onboarding.Liveness Detection serves as a preventive measure against fraud attempts using static images or prerecorded videos. On the other hand, Face Matching plays a crucial role in ensuring the accuracy of identity verification. It achieves this by comparing live images captured during the onboarding process with reference images or identity documents, validating the authenticity of the individual’s identity.

These technologies not only enhance security but also improve the customer experience during the digital onboarding process. By automating identity verification through Liveness Detection and Face Matching, financial services providers can offer a seamless and efficient onboarding experience for customers. This automation eliminates the need for manual document submission and in-person visits. Instead, customers can conveniently complete the verification process online, saving time and effort while maintaining a high level of security and accuracy.

In summary, Liveness Detection and Face Matching technologies have revolutionized the digital onboarding process, ensuring security, reducing fraud risks, and improving the overall customer experience. By leveraging advanced computer vision and machine learning capabilities, these technologies provide a robust solution for accurate identity verification, helping financial services providers establish trust and confidence in the digital realm.

QuickSign provides state of the art KYC for financial services, including Liveness Detection and Face Matching (LDFM). Read on for more information or contact us to find out how to apply LDFM to your digital onboarding experience. 

Written by Tristan L.

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