Speech recognition: the next great disruptive tech for financial services

Woman using voice assistant on smartphone in the rain

From the rise of mobile banking to the advent of vehicle telematics, technology has proved itself to be both a continued disruptor and a ongoing opportunity in the financial services industry.

The companies that thrive in this climate are the early adopters, the disruptive startups, and fast-moving incumbents that embrace new tools to serve customers in new ways, offer new products, and create low-friction, high-satisfaction experiences.

But there’s one technology that can transform not just customer experiences but operational efficiency. And though many financial services professionals will have encountered it at some point in their careers, it remains relatively untapped by financial services providers.

Speech-to-text: a financial services disruptor in waiting

Speech recognition technology has been around for a long time, and it’s improved dramatically in recent years, especially with advances in AI-led natural language processing. These days, it is fast and accurate without any training—and it has far more applications than you might expect.

Let’s take speech-to-text, for example. These tools are increasingly commonplace in the legal and healthcare industries, where they let professionals focus on interacting with clients or patients rather than typing up notes.

This can have a profound impact on their productivity, for the simple fact that people speak three times faster than they type. Most of us can reliably type around 40 words per minute, while the speaking average is closer to 130 words per minute. Even for professional typists, that kind of speed is virtually impossible to match with a keyboard.

With the right speech-to-text tool, financial advisors, accountants, auditors, brokers, and back-office support staff alike can take notes, complete documentation, and even fill in forms using just their voice. And the time they save on admin work can be spent on more valuable tasks—building meaningful customer experiences that boost satisfaction and retention.

What’s more, when notes are taken in real-time rather than typed up later, they tend to be more detailed and more accurate—contributing to more complete audit trails and more compliant processes.

A technology that’s come of age

Our latest speech-to-text recognition engine, used in our Dragon solutions, can achieve up to 99% accuracy out of the box and automatically adjusts to users’ accents and pronunciations for even greater accuracy over time. You can even tailor its dictionary to add finance-specific terminology and push these updates to a whole team with a single click.

But there’s another reason why speech-to-text has recently come of age for financial services applications. It’s now available in the cloud, with all the security and IT admin and mobile working benefits that it implies. With its Microsoft Azure backend and AES 256-bit encryption, our cloud-based Dragon Professional Anywhere solution protects data in transit and at rest.

Where the disruption has already begun

While the productivity revolution possible with speech-to-text is only just beginning to take hold within financial services, some brands lead the way with customer-facing applications of speech recognition technology.

Interactive Voice Response (IVR) technology has been a staple of customer service for decades—but it’s often been a source of friction and frustration for customers, as they’ve struggled to navigate their clunky menu trees and “Dual Tone Multi-Frequency” (DTMF) systems. In recent years, however, speech recognition technology has helped to transform many FSI IVR experiences. Combined with conversational AI, advanced speech recognition allows customers to have a human-like discussion with the IVR, explaining their needs in their own words for faster resolutions and improved self-service containment.

Speech technology can underpin the security of modern IVRs, too. More and more FSIs are using voice biometrics to help them prevent fraud by authenticating customers—or identifying criminals—based on the sound of their voice.

At Virginia Credit Union, more than 160,000 customers have signed up for its biometric authentication program, which uses Nuance Gatekeeper to recognize characteristics unique to their voice. Instead of remembering PINs, passwords, or answers to secret questions, its members can simply start talking. If their voice isn’t recognized or matches a watchlist of fraudsters’ voices, this is flagged to the agent to take appropriate next steps.

Verifying a caller used to take more than two minutes, but with voice biometrics, and that’s now down to as little as three seconds, saving 90 seconds, on average, per call. More than 79,000 confirmed IDs in the first year of the program have helped the credit union prevent fraud attempts and boost satisfaction for customers and agents.

Embrace the potential of speech

From enabling conversational customer interactions with an intelligent IVR system, to completing reports and correspondence through speech-to-text, voice-based technologies have many compelling applications for the modern FSI.

They can save time for employees and customers alike—but they can also support more accurate documentation and more straightforward, more robust security and compliance. The trick is finding the right, enterprise-grade tools and a technology partner that understands your industry and is ready to help you break new ground.

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Ed McGuiggan

About Ed McGuiggan

Ed McGuiggan is General Manager for the Dragon Professional and Consumer business, overseeing the strategy for Nuance's Dragon speech recognition and documentation product line. Ed has held various leadership roles within Nuance over the past two decades, including the creation, development, and expansion of the company’s worldwide eCommerce business, as well as the management of the Corporate and Retail sales teams. Prior to joining Nuance in 1997, Ed held senior management roles at FTP Software and Corporate Software, Inc. He holds a Bachelor of Science Degree in Mass Communications from Emerson College.