As AI becomes more sophisticated, organizations can leverage it in new ways.
For instance, it now understands the thousands of nuances in human speech to identify the person speaking entirely without manual intervention. This is what voice biometrics aims to achieve.
In doing so, it assigns a voiceprint to every customer or prospect. The AI then matches the customer’s voice to a stored voiceprint for user authentication.
As a result, voice biometrics streamlines identification and verification (ID&V) processes, lowering customer effort in the process – often significantly.
A Unisys study supports this assertion, highlighting how voice recognition is the most popular method of authentication amongst consumers, followed by fingerprints and a facial scan.
Yet, how can businesses best deploy the technology, and how effective is it? Let’s find out.
What Is Voice Biometrics?
Voice biometrics is a technology that enables identity verification by analyzing a person’s voice as a unique, innate characteristic.
It starts by storing a voice input sample in the system, just like a smartphone stores its user’s fingerprint for authentication.
Later, when the person speaks into the voice biometrics software, it splits the audio statement into multiple frequencies.
In doing so, the voice biometrics software examines the behavioral attributes, comparing them with the sample stored in the system.
There are two types of authentication that can take place through voice biometrics:
- Text-Dependent Authentication – The customer utters a specific phrase stored in the system as a sample. In the future, the customer must remember and repeat this exact phrase for smooth authentication.
- Text Independent Authentication – The analysis happens purely based on the characteristics of the customer’s voice, not the specific contents of what they are saying. This type of voice biometrics can run in the background as the agent speaks to a customer. It is also known as passive voice biometrics.
The Benefits of Voice Biometrics in a Contact Center
Voice biometrics can dramatically improve contact center efficiency by mitigating fraud risk, shrinking call durations, and improving self-service adoption.
By having customers authenticate themselves through voice biometrics, businesses can ensure that agents do not reveal confidential information to someone impersonating a customer.
Moreover, an automated voice biometrics-based authentication system frees agents from manually checking customer identity. The system could also auto-lookup contextual customer information, further saving time.
Finally, voice biometrics could drive up IVR self-service rates. Despite IVR self-service being much more cost-efficient than live agents, it often resolves only a small percentage of all calls.
Why? Most often because the customer has already attempted solving their issue through digital self-service before picking up the phone.
However, among other reasons, some customers consider IVR less secure than live agents. Voice biometrics may eliminate this risk and inspire confidence.
In doing so, it can shrink call queues and reduce agent workloads.
How Effective Is Voice Biometrics?
Alongside those in the contact center, voice biometrics supports further fraud detection use cases and enables new customer capabilities. Digital signatures are an excellent example.
Yet, is it failproof? Not always. Indeed, there are instances wherein a system may be unable to effectively recognize a person’s voice, such as when they have a cough or a cold.
There is also a risk that people could bypass a voice biometrics system by using a recording of another person’s voice. However, leading providers of biometric software are currently experimenting with ways of eliminating this risk.
Additionally, many modern voice biometric systems also come with continuous authentication strategies. Such strategies ensure that the software listens into the entirety of the customer conversation. This ensures that a second speaker does not take the reigns.
However, a new threat is emerging: voice spoofing. This aims to trick biometrics systems into believing they are listening to the real, authenticated customer. Nevertheless, in actuality, it is an AI bot.
Thankfully, voice biometrics players are also working to negate this issue, launching new solutions – such as Void (Voice liveness detection) – to differentiate between bots and humans.
As these solutions grow in maturity, accuracy, and security, expect more companies to experiment with voice biometrics and streamline the customer experience.
Learn more about how to implement voice biometrics by reading our article: Replacing Passwords and PINs with Voice Authentication
