Biometric authentication encompasses technologies and practices for measuring and analyzing an individual’s unique physical and behavioral characteristics. Although it’s a long-established practice, adoption remained relatively low until recently. Today, however, with the proliferation of the Internet and digital devices, many organizations are increasingly favoring biometric authentication, resulting in even more advanced technologies.
Among the latest trends in biometric authentication is the incorporation of AI and machine learning. One of the biggest challenges of biometrics is inaccuracy. This is changing, thanks to AI.
Now, machines can learn from individual data, reducing false positives and negatives. That means AI-powered biometric authentication machines will be able to keep up with an individual’s age-related physiological changes. Biometric systems will become smarter, faster, and more responsive.
Until recently, banks and other institutions relied on one or two biometric authentication methods. More are being used today, thanks to multimodal biometric systems. As cyber attackers and other digital criminal actors adopt advanced tools, institutions must keep up by combining various authentication protocols, such as facial and voice recognition and fingerprints.
Multimodal systems will soon become the norm in high-security areas. Spoofing is one of the most common ways that attackers use to gain access to a restricted area, posing as a trusted user. With multi-modal biometric authentication, a photo won’t be enough to pass through security. Incorporating real-time verification and liveness detection will significantly limit identity fraud.
Many companies treat identity proofing as a one-off affair. An employee, for example, may go through identity proofing during onboarding, receive access controls, such as passwords, and it ends there. That’s changing, thanks to continuous authentication.
Continuous authentication enhances know your employee (KYE), ensuring an organization continuously verifies a user’s identity, not just at the point of entry. This trend is proving useful in sensitive environments, where even a brief unauthorized access can have far-reaching implications. For example, some systems periodically take a photo of the user, screenshot their screen, and monitor typing patterns and location to ensure they remain the authenticated user throughout the session.
Remote work is becoming the norm in many organizations. One of the technologies making that possible is touchless biometrics. Tools such as facial recognition and iris screening allow organizations to accurately and reliably identity-proof candidates and employees. Hands-free biometrics are also useful in environments where hygiene or speed is key, such as airports and hospitals.
A key aspect of biometrics, and one that many traditional systems neglect, is behavioral characteristics. Behavioral biometrics changes that. It identifies individuals based on their unique behavioral traits.
Behavioral biometrics analyzes physical features, such as posture and walking style. It may also include capturing and analyzing emotional responses. Because it can detect out-of-character actions, it may catch forced authentication, for example, when an individual is made to e-sign a document.
Even with advances in biometric tools and approaches, the risk of data breach remains due to centralized data storage and processing. Edge computing and blockchain-based authentication promise to reduce data exposure through device-based authentication.
In addition to limiting the risk of data breach, edge-enabled authentication reduces latency. Blockchain-enabled authentication uses unalterable private keys to verify the authenticity of devices, individuals, and transactions, thus preventing identity theft and fraud.
Even as biometric uptake increases, access remains a challenge for small businesses. Meanwhile, questions around data privacy and user security linger. The potential misuse of biometrics for unauthorized surveillance raises weighty ethical and moral concerns. Clear governance, coupled with user-centric privacy-first identity management, is key to pushing the boundaries of biometrics while minimizing friction.







