How Voice Biometrics is positioned for quick uptake in the new Internet of Everything
Society is moving from “The Internet of Things” to “The Internet of Everything”. This is a world in which most processes are mediated through data transfer, where human interaction has a permeable data flow attached to it, and algorithms are deployed to manage the seamlessness of this superstructure.
With the rapid onset of urbanisation and digitisation, there is parallel growth in the telecoms industry. This means that new methods of multi-factor authentication are required to facilitate the smooth everyday operations that we expect from this new surge in technology, and counter the simultaneous increase in vulnerabilities to cyber-attacks and identity fraud.
Modern cyber-criminals are masters of disguise, and the evergreen-growth of the number of interface points means this seamlessness must come without sacrificing security. Voice Biometrics is one of the best innovations for exactly this.
At its root, it is the matching up of a voiceprint to a timestamped login. The voiceprint is a mathematically constructed representation of a voice’s sound. By using an AI to match up the voiceprint, security is greatly enhanced, because impersonation, or fooling the AI, is nigh-on impossible. It’s the physical characteristics of someone’s larynx that provides complexity of the lock and key, not a knowledge-based password that can be worked out, written down, or hacked - it’s harnessing the power of evolution for technological use. If it sounds futuristic, it’s because it’s part of the ongoing revolution of algorithmic culture.
What’s more, if the Voice Biometric system is easy to integrate into pre-existing architectures, such as into Cloud-based systems, it can be defined as inherently adaptable, and helps drive new innovations in telecoms. The onboarding process for Voice Biometrics is a prime example - performed actively, by the user repeating a passphrase (“my voice is my password”), or passively, with consent, in conversation with customer service agents or IVR systems.
As to its resilience, the highly developed algorithms that perform the matching-up are self-learning, adapting automatically for each speaker individually. This means they are better able to distinguish background noise from voice, characteristics of microphone, and distortion along the phone signal with each use.
The current lay of the land
So how far along is the world in adopting Voice Biometrics into telecoms at the moment? There is definitely an increasing demand. In fact - the Voice Biometrics market is expected to grow to reach $3.91 billion by 2026.
There are a couple of interesting factors at play here: whether pre-existing system architectures can integrate Voice Biometrics, and whether the public are ready and willing to adopt it. As previously mentioned, Biometric solutions are indeed quite like something out of science fiction. We are already seeing a concurrent rise of Conversational AI. As platforms like Siri and Alexa are adopted into global culture, navigating the digital with one’s voice is increasingly normalised.
Generational differences also make up both the push and pull factors of Voice Biometric adoption: “Younger adults are putting less care into traditional password hygiene [using the same password across multiple domains], yet are more likely to use biometrics, multifactor authentication and password managers ... Older generations showed more care with password creation, but were less inclined to adopt biometrics and multifactor authentication.” This point could be that more is needed to address the not-unfounded scepticism surrounding data privacy of biometric data, by making the onboarding process equally as transparent as it is seamless and simple.
By doing this, Voice Biometrics can be considered as a key player in continuing to develop and enhance the seamless technological interaction that people, especially ‘digital natives’ have come to expect and demand, whilst also bringing a highly secure and resilient technology to the forefront of the digital.
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