Liveness Detection in KYC Changing the Online Identity Verification

Identity verification is one of critical importance beyond safety estimation. However, cybercriminals are constantly producing new methods, due to the previous KYC techniques lacking in fighting against fraud and impersonation. Therefore, liveness detection has emerged as an absolute game-changing solution that provides the latest biometric verification and facial recognition technology. 

Besides, the presentation attack detection acts as an important security layer to fight against identity theft in virtual transactions and digital verification methods. The ability to differentiate between authentic users and fraud attacks reinforces the huge protection and trust. Let’s explore how advanced technology has transformed the role of live-presence detection to increase authentication, alongside the influence of fraud prevention, and other important components while choosing the liveness detection partner.

Development of KYC in the Virtual Age

The emergence of KYC methods in the digital age ensures how tech breakthroughs have reshaped safe and smooth identity verification methods. Furthermore, the integration of liveness detection technology, ML, blockchain, and 5G communication has prominently increased KYC’s success and flexibility. From fighting against forgeries via handwritten signature authentication while using CNN to upgrading the secure transaction with 5G has enabled identity verification. Also, these innovations are elaborating the digital banking levels in the digital age. Blockchain itself is a peer-to-peer and manipulation-resistant design. Besides, blockchain is working as old manual KYC methods that provide several data ethics and success. These technologies are changing the KYC into a stringent structure that promotes the financial organization to execute a safe and smooth experience in the digital age. 

Liveness detection is one of the important factors of recent identity verification systems, reinforcing that posing identity truly belongs to the real person. The real-time verifications are easy to track from the idea of Alan Turing, a renowned mathematician. His 1950s Turing test estimated the machines’ proficiency to express human-like intelligence. The main focus of the test is to recognize human-like feedback from computers. 

The test’s rules are resonating with the recent liveness detection techniques. The system pretends as the “player” in the Turing test during the immediate verification, recognizing if the applicant is a real human or a spoof. Apart from this, some experts are connecting the term “liveness detection” to the Dorothy E test. In a 2001 article, Denning showed the biometric systems’ need to analyze the liveness that relates to humans as they recognize each other.   

In recent times, digital verification has been usually executed during digital identity verification methods. These methods frequently demand the users to provide a real-time selfie. However, this step reinforces that the person engaging with the technology is present in reality. 

Types of Liveness Detection

The biometric liveness detection depends on the user interaction level:

1. Active Liveness

In the early days, genuine user detection systems depend on the active interaction while asking the user to act on some particular actions. For instance, eyes blinking, smiling, or head-turning actions are involved in this process. These actions are useful in fraud detection, but it’s not user-friendly for older people. 

2. Passive Liveness:

This type of detection reduces the extra actions’ requirements and makes the techniques smooth. It requires the user to provide a pre-existing selfie while allowing the system to examine their liveness and use the facial recognition algorithms. Furthermore, the flexibility of high-resolution images is challenging for users during the use of low-resolution devices. 

3. Hybrid Liveness:
Combining the attributes of an active and passive approach, therefore, hybrid liveness detection preserves security requirements with associated convenience. For example, one may require that a user snaps a selfie during a short required action like a smile.

How Liveness Detection Works

The major purpose of the liveness detection solution is to detect fraud attempts, for instance, deepfakes, images, and forged videos alongside silicon-based mask impersonation. The biometric verification systems utilize the latest neural networks that are trained on huge datasets to check the minor details that show whether the person is real. 

Such systems can detect spoofing artifacts such as:

• 2D printed photos or paper masks
• Human-like dolls, latex, or 3D masks
• Digital artifacts like glare or shadow inconsistencies from deepfakes

The liveness detection algorithms create facial maps in either 2D format as (X, Y) or 3D format as (X, Y, Z). Generally, for efficiency, many passive systems use the 2D mapping of the faces while active systems use 3D mapping for increased security, especially in payment approvals.

It is not limited to facial recognition. Voice liveness detection, for instance, examines audio patterns to filter out live speech from pre-recorded samples or AI-generated voices. No matter which biometric factor is used, the basic purpose remains the same: to confirm that the data originates from a living person.

Advantages of Real-Time Detection in KYC 

Liveness detection in KYC follows the latest spoofing mitigation process like checking the facial texture, slightest movement, and light reflections, efficiently protecting the fraudsters from fooling the system with the fabricated identities. Let’s discuss some of the other benefits of real-time detection in KYC:

• By checking the appearance of authentic humans during online onboarding, liveness checks KYC reduce the generation of fake accounts. 
• Moreover, the liveness checks go beyond the starting phase of verification, reinforcing the user’s appearance via KYC methods to enhance safety and fraud protection. 
• Biometric verification in KYC provides reliable remote authentication and allows users to accomplish identity verification safety across the world. 
• The method is smooth and user-friendly, and passive liveness detection runs in the background. It offers a hassle-free user experience.  
• Liveness check KYC supports businesses in following the rules and regulations and in complying with regulations related to secure and lawful verification processes.
• The examination of even the smallest features and expressions can be done, thus enhancing the security of eKYC systems by making them highly reliable and robust.
• Completely automated liveness checks increase the speed as well as cost efficiency of the KYC process by limiting the possibility of identity theft and consequential financial loss.

Industries Leveraging Liveness Detection

Liveness detection has become the most valuable tool in every industry worldwide to enhance safety and smooth operations. Therefore, industries like financial sectors are openly using it to reduce fraud during virtual onboarding and safe transactions.  Besides, the healthcare industry also uses this technology to defend their sensitive patient data and enable safe telemedicine counseling. Liveness detection changes and improves businesses through identity verification. For e-commerce, it is used to protect high-value transactions. Aviation and travel rely heavily on liveness detection for passenger verification as well as border control. The government, education portals, and gaming sectors use it to ensure security, prevent fraud, and authenticate users flawlessly.

Challenges and the Future of Liveness Detection in KYC

Challenges

Previous liveness detection systems experienced multiple challenges that blocked consistency and safety. Also, the previous methods involved the weakness of the high-resolution deepfake detection and 3D silicone masks that can easily fool the fundamental checks. 

Furthermore, sometimes the light conditions, the slightest facial change due to aging, or changes in the facial hair can decrease the systems’ accuracy. Besides, injection attacks or presentation attacks are previously recorded visuals or high-resolution prints that examine the systems’ strength. Critical to the secure verification of identity is the need for advanced algorithms and techniques that fill in such lacunas.

Solutions

Advanced liveness detection solutions address these challenges through multi-modal approaches, real-time 3D scanning, and robust anti-spoofing measures to considerably improve accuracy and security through analysis of dynamic facial cues, texture variations, and behavioral biometrics.

Best 3D Face Liveness Detection:

On the other hand, FACIA is helping the real users onboard while keeping fraudsters at bay using powerful spoof detection technologies.

• Below 1 Second Response Time
• On-Prem and Cloud Integration
• Certified iBeta Level 2 Solution

Counter over 56 types of spoofing attacks and ensure safe and smooth onboarding today with KYC. so, explore how Facia can change your future of KYC: unmatched security.