Voice Biometrics in Financial Services: How It Works

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Brian Martin, Regional Director UK & Ireland, Spitch

How does voice biometrics technology work in the financial services industry?
Brian Martin, Regional Director UK & Ireland, Spitch

Recognising the spoken word can be a challenge for financial businesses, as time-consuming customer interactions can turn into a costly process. Voice biometric solutions are designed to address this problem. They use algorithms to process and analyse interactions precisely and in real-time, to bolster businesses’ back-end knowledge bases. The use of voice has grown exponentially in recent years, with the voice recognition market estimated to be worth $601 million by 2019. Deploying this technology in contact centres alongside traditional points of contact enables businesses to carry out a variety of functions, including client identification, identity authentication, and semantic interpretation. All of this means businesses can be more effective and efficient in their interactions with consumers.
What are the business benefits of voice biometrics?
There area number of cases and scenarios where speech analytics and natural language processing (NLP) can add value. It enables real-time detection of customer frustrations, which can help identify the root causes of customer experience failures. It can also be used for competitor analysis and can be a useful tool for tracking customers wants and needs against the service delivered.
Perhaps most significantly, it can be used to identify and verify customer identities in natural conversation. This is more secure than other emerging biometric authentication methods such as fingerprints, because an individual’s voice is defined by 82 different characteristics – including tone and depth – which makes the properties of a voice harder to reproduce. Not only does voice biometric verification help in the fight against identity fraud, but it also reduces customer call times through bypassing the need for security questions.
What are the main challenges facing voice biometrics in this sector?
The technology learns continuously and automatically through its interactions with customers, but this can occasionally leave it susceptible to misinterpret that which it is unfamiliar with. In this respect, local dialects and irregular sequencing of language can cause the occasional problem. However, automated learning means these issues will be addressed and overcome quickly through usage, as the technology has already demonstrated since its conception, with error rates dropping from 43% in 1995, to just 6.3% in 2017.
How should financial institutions be approaching voice biometrics?
Businesses should see voice biometrics as an untapped resource and a source of competitive edge. This technology does not need to replace people – it can amplify and enhance human capabilities by giving us a more intuitive way to interact with customers. The technology is still emerging in the financial sector, and the sooner businesses can implement it within their operations, the sooner they can begin to benefit, whether that’s through improving the level of customer service offered in contact centres or reducing operational costs.
With GDPR approaching, how can voice biometrics help businesses achieve compliance?
Businesses collect masses of customer data over the phone, especially since call recording has become standard practice for customer interactions. The problem is, none of this data is stored in a searchable format, which makes dealing with customer data requests a laborious process. For instance, finding out when a customer gave their address over the phone could potentially require hours of tedious manual trawling through call logs. Under the threat of significant fines, these inefficient processes will no longer be tenable when GDPR comes into effect.
Voice biometrics solve this problem. Using speech-to-text solutions, for example, businesses can take a phone call and convert it into an immediately searchable digital format. This means businesses can quickly keyword search through all correspondence to pinpoint customer information in a text format, which can be shared easily with that individual on request.
What’s the future for this technology in the financial sector?
Businesses are beginning to realise the potential of voice biometrics technology, which will contribute to it becoming a mainstay in the financial services sector.And this reality isn’t far off. In 2018, a growing number of consumers will access financial products, get answers to concrete questions, and more – all made easier though voice recognition technologies, which will analyse speech automatically during consumers interactions with mobile apps, call centre robots, or to fellow human beings. Voice recognition technology is available now, and by adopting it early, businesses in the financial services sector can ensure they use it to its full potential before it becomes standard practice.

Brian Martin, Regional Director UK & Ireland, Spitch

How does voice biometrics technology work in the financial services industry?
Brian Martin, Regional Director UK & Ireland, Spitch
Recognising the spoken word can be a challenge for financial businesses, as time-consuming customer interactions can turn into a costly process. Voice biometric solutions are designed to address this problem. They use algorithms to process and analyse interactions precisely and in real-time, to bolster businesses’ back-end knowledge bases. The use of voice has grown exponentially in recent years, with the voice recognition market estimated to be worth $601 million by 2019. Deploying this technology in contact centres alongside traditional points of contact enables businesses to carry out a variety of functions, including client identification, identity authentication, and semantic interpretation. All of this means businesses can be more effective and efficient in their interactions with consumers.
What are the business benefits of voice biometrics?
There area number of cases and scenarios where speech analytics and natural language processing (NLP) can add value. It enables real-time detection of customer frustrations, which can help identify the root causes of customer experience failures. It can also be used for competitor analysis and can be a useful tool for tracking customers wants and needs against the service delivered.
Perhaps most significantly, it can be used to identify and verify customer identities in natural conversation. This is more secure than other emerging biometric authentication methods such as fingerprints, because an individual’s voice is defined by 82 different characteristics – including tone and depth – which makes the properties of a voice harder to reproduce. Not only does voice biometric verification help in the fight against identity fraud, but it also reduces customer call times through bypassing the need for security questions.
What are the main challenges facing voice biometrics in this sector?
The technology learns continuously and automatically through its interactions with customers, but this can occasionally leave it susceptible to misinterpret that which it is unfamiliar with. In this respect, local dialects and irregular sequencing of language can cause the occasional problem. However, automated learning means these issues will be addressed and overcome quickly through usage, as the technology has already demonstrated since its conception, with error rates dropping from 43% in 1995, to just 6.3% in 2017.
How should financial institutions be approaching voice biometrics?
Businesses should see voice biometrics as an untapped resource and a source of competitive edge. This technology does not need to replace people – it can amplify and enhance human capabilities by giving us a more intuitive way to interact with customers. The technology is still emerging in the financial sector, and the sooner businesses can implement it within their operations, the sooner they can begin to benefit, whether that’s through improving the level of customer service offered in contact centres or reducing operational costs.
With GDPR approaching, how can voice biometrics help businesses achieve compliance?
Businesses collect masses of customer data over the phone, especially since call recording has become standard practice for customer interactions. The problem is, none of this data is stored in a searchable format, which makes dealing with customer data requests a laborious process. For instance, finding out when a customer gave their address over the phone could potentially require hours of tedious manual trawling through call logs. Under the threat of significant fines, these inefficient processes will no longer be tenable when GDPR comes into effect.
Voice biometrics solve this problem. Using speech-to-text solutions, for example, businesses can take a phone call and convert it into an immediately searchable digital format. This means businesses can quickly keyword search through all correspondence to pinpoint customer information in a text format, which can be shared easily with that individual on request.
What’s the future for this technology in the financial sector?
Businesses are beginning to realise the potential of voice biometrics technology, which will contribute to it becoming a mainstay in the financial services sector.And this reality isn’t far off. In 2018, a growing number of consumers will access financial products, get answers to concrete questions, and more – all made easier though voice recognition technologies, which will analyse speech automatically during consumers interactions with mobile apps, call centre robots, or to fellow human beings. Voice recognition technology is available now, and by adopting it early, businesses in the financial services sector can ensure they use it to its full potential before it becomes standard practice.