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Fraud Prevention Smile ID News25 Feb 2024

Understanding the role biometrics plays in Identity Verification - Insight from the Smile ID Digital Identity Fraud Report

Gift Arku

Marketing Intern

Understanding Biometrics

Biometrics refers to the measurement and analysis of individuals' unique physical or behavioural characteristics. These characteristics are often used for identification or authentication purposes. Examples of biometric identifiers include fingerprints, facial features, iris patterns, voiceprints, and even behavioural traits such as typing patterns or gait. 


Biometric authentication systems compare these unique characteristics against stored templates to verify the identity of individuals. Biometrics is widely used in various applications, including access control, identity verification, time and attendance tracking, and security systems.


Biometric Fraud 

As most African countries move towards stronger ID documents with biometric security, fraudsters are evolving their methodologies. Biometric fraud is usually more complex than document fraud and difficult to catch without advanced prevention tools. It involves the unauthorised and fraudulent use of biometric data. It is often performed in tandem with document fraud to trick biometric systems into accepting fraudulent data. While there are many ways that biometric data can be manipulated for identity fraud, most biometric fraud generally falls into four categories

  • No-Face Match 

  • Spoofing 

  • Generative AI (Deep Fakes) 

  • Duplication

Facial Recognition vs. Fingerprint Biometrics

Among the various biometric fraud prevention methods, fingerprint and facial recognition are the most adopted based on several factors such as accuracy rates, current technological advancements, scalability and usability. Although fingerprint recognition boasts a high accuracy rate, it encounters scalability challenges due to hardware requirements. 


In contrast, facial recognition has gained prominence for its scalability and accuracy, driven by advancements in deep learning algorithms and the ubiquity of image-capturing devices. It is also just as accurate as fingerprint biometrics. 


Facial recognition technology leverages the abundance of facial image databases and computational power to achieve remarkable accuracy scores. Unlike fingerprint scanning, which necessitates specialized hardware, facial recognition can utilise standard smartphone cameras, making it more accessible and user-friendly. 


Some of the fundamental differences between facial recognition and fingerprint that make facial recognition the most sustainable method of preventing biometric fraud include: 


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Advantages of Liveness Detection to Selfie Comparison in Facial Recognition

We established that facial recognition is the most advantageous form of verifying biometric identity. Now let’s explore the nuances within facial recognition; Selfies vs Liveness. 


Liveness detection is the best strategy to enhance security. Unlike static verification methods like selfies, liveness tests require users to perform spontaneous actions, such as blinking or smiling, to confirm real-time presence. This proactive approach significantly reduces vulnerability to spoofing attacks and synthetic media, enhancing overall security.


Combatting Biometric Fraud

Despite the strides made in biometric technology, fraudsters persist in devising sophisticated schemes, which means as fraudsters continue to get sophisticated, you should too. Biometric fraud exploits vulnerabilities in biometric systems, underscoring the importance of robust security measures.


In navigating the intricacies of biometric identity verification, embracing facial recognition technology with active liveness detection is your best bet. 


Smile ID's biometric solutions seamlessly include active liveness detection. Our system uses Machine Learning Algorithms to find and stop deep fakes. With our Smile Secure add-on, we prevent duplicate accounts by identifying users who've been verified before, even if they use different identities. Also, our Active Liveness feature ensures user authenticity by asking users to smile during verification, making it harder for fraudsters to deceive the system.


For further insights on all things Fraud in Africa, refer to our comprehensive digital identity fraud report. Download it for free here.

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