The Role of Voice Biometrics in Enterprise Security Systems

17.03.2021

Voice Biometrics in Enterprise Security Systems

Artificial Intelligence (AI) has been around for decades. However, we didn’t reap its true benefits until recently. With chatbots, voice bots, and more, AI is now a force to be reckoned with.

When we think of AI-based voice systems, we think of voice-based assistants Alexa and Siri. These voice assistants engage in Internet searches, switch lights on and off, play music at our homes and just make life a little easier. However, speech recognition isn’t the same as voice biometrics.

What is Speech Recognition?

Speech recognition is focused on understanding the meaning of what we’re saying. That’s why we can ask questions like, “Hey, Alexa, what’s the weather forecast today?”. In this scenario, smart algorithms will understand the question and then search for an answer using a search engine (just like us!).

Tip:
multi-faceted and needs-specific audio data sets for speech recognition training can be simply ordered at clickworker.

As such, some people have already integrated voice assistants into their daily routine. So it makes sense that AI-powered voice-based solutions will also enter the workplace, enhancing the cooperation between human and machine.

According to Gartner, as much as 70% of white-collar workers will engage and interact with conversational platforms by next year. This means that voice-based smart systems are rapidly getting more sophisticated. This year, Gartner expects 25% of digital workers to use virtual employee assistants on a daily basis. This is especially great for those working remotely from home in the “new normal”.

What is AI-Based Voice Biometrics?

Voice biometrics concentrates on who’s talking and not necessarily what they are saying. It’s essentially a tool used to establish a person’s identity. In this scenario, AI and ML algorithms study the user’s unique vocal characteristics and compare them to established patterns.

With voice biometrics, you can measure a person’s non-visual characteristics for security and authentication with 90% accuracy. These non-visual vocal characteristics include the following:

Notable financial services institution that leverage voice biometrics for authentication and telebanking include:

  • Accents
  • Emphasis
  • Pronunciation
  • Speed of speech
  • Vocal cord

Voice biometrics in security and authentication occurs in two stages. In the first stage, the user’s voiceprint is created and converted into an easily readable format. In the second stage, neural networks train continuously and compare the voiceprints.
Developers place the resulting voiceprints in frames that are clear of external factors such as background noise. These clean frames are then added to a database for comparison during a security and authentication exercise.

AI-Powered voice biometrics is a growing niche within enterprise security. Just like deep artificial neural networks learn to recognize faces, ML algorithms learn to imitate our brain mechanisms and interpret voice data (sometimes used along with image and text).

Deep Learning (DL) is important because it improves accuracy and ensures that only the intended user activates critical functions. Furthermore, it also plays an important role in fraud prevention.

Leading voice biometrics solutions include:

Notable financial services institution that leverage voice biometrics for authentication and telebanking include:

  • ArmorVoxTM
  • B-Secur
  • Daon
  • NICE
  • Nuance Communications
  • Uniphore Software Systems
  • Verint Systems
  • Voicekey

How Does AI-Powered Voice Biometrics Work in Fraud Prevention?

One of the most common methods used by threat actors is impersonation. For example, they call a bank and impersonate a customer, requesting changes of addresses, phone numbers and so on. If the customer service agent fails to ask authentication questions, the fraudster has access to all messages intended for the victim.

From here on out, criminals can access sensitive information, including real-time payments. While banks have security protocols that are alert to suspicious activity, transfers of small amounts of money may not be quickly identified and blocked by the customer’s bank. But with voice biometrics, threat actors won’t get as far as that stage.

Notable financial services institution that leverage voice biometrics for authentication and telebanking include:

  • Charles Schwab
  • Chase
  • Halifax
  • HSBC
  • Lloyds Bank
  • Wells Fargo

Voice authentication also equals a significant reduction in call length. As you won’t be paying customer service agents to repeatedly ask the same security questions, it also leads to substantial savings. Other benefits include enhanced customer experiences and regulatory compliance.

The voice biometrics technology was developed specifically for financial services and online banking, but the pandemic has opened up new opportunities. For example, we now have a significant interest in biometric voice systems in the education sector.

In this scenario, voice biometrics can be applied along with other security protocols to confirm a student’s identity, especially during an online exam. Combined with other AI-powered security tools like facial recognition, voice-based AI systems may look for acoustic patterns, match them to human appearance and behavior to authenticate users faster, reduce false alarms, and more.

However, these ideas and concepts are still in their infancy. While continuing to live in the “new normal”, we can expect voice-based authentication to accelerate across industries. As these smart algorithms mature, so will their impact on our overall security.

 

Dieser Artikel wurde am 17.March 2021 von Andrew Zola geschrieben.

avatar

Andrew Zola