Mastercard’s Shift to Biometric Payments: Why Voice Biometrics and Deepfake Detection Are Essential

Mastercard moves beyond card numbers: Why integrating voice biometrics ensures secure and seamless remote transactions.

In a significant stride towards enhancing payment security, Mastercard has announced plans to eliminate 16-digit card numbers from credit and debit cards by 2030, transitioning towards biometric-powered transactions.

This initiative aims to reduce reliance on physical cards and static passwords, integrating tokenization and biometric authentication methods such as facial recognition and fingerprints.

While facial and fingerprint biometrics are effective for in-person transactions, they fall short in remote interactions, particularly within contact centers, Interactive Voice Response (IVR) systems, and Intelligent Virtual Assistants (IVA). In these voice-driven environments, voice biometrics emerge as the most viable authentication method, offering a seamless and secure user experience.

The Imperative for Voice Biometrics in Contact Centers

Contact centers are increasingly targeted by fraudsters employing sophisticated techniques, including AI-generated voice deepfakes. These synthetic voices can mimic legitimate customers, bypassing traditional security measures and leading to unauthorized access and financial losses. Implementing voice biometrics allows organizations to analyze unique vocal characteristics, ensuring that the speaker’s voice matches the authenticated profile. This method not only enhances security but also streamlines the customer experience by reducing reliance on cumbersome security questions.

Combating Deepfake Audio Threats

The rise of deepfake technology has escalated the need for robust audio verification systems. Fraudsters can now create highly convincing synthetic voices, making it challenging to distinguish between genuine and fake callers. To address this, advanced deepfake audio detection solutions have been developed. For instance, ValidSoft’s Voice Verity® technology monitors calls in real-time, utilizing sophisticated algorithms to identify synthetic audio generated by AI. This ensures that any call placed to a contact center is verified as being human, providing an essential layer of protection against deepfake attacks.

Integrating Voice Biometrics and Deepfake Detection

For a comprehensive security framework, it’s imperative to integrate voice biometrics with deepfake audio detection. While voice biometrics authenticate the speaker’s identity, deepfake detection systems assess the authenticity of the audio, identifying and mitigating synthetic voice attacks. This dual approach ensures that both the identity of the speaker and the genuineness of the voice are verified, fortifying defenses against increasingly sophisticated fraud attempts.

As the financial industry progresses towards a cardless and password-free future, embracing a holistic biometric strategy is crucial. While facial and fingerprint recognition serve well in physical interactions, voice biometrics combined with deepfake audio detection are indispensable for securing voice-based channels and for enabling self-service across a variety of current and new use cases, such as: ordering new/replacement cards; activation of the card on receipt; reporting fraud; voice-activated payments, to mention a few. This integrated approach not only safeguards against fraud but also enhances the overall customer experience, aligning with the evolving landscape of digital transactions, whilst also achieving transaction irrevocability, non-repudiation, and data immutability.