Banking
How to Use AI to Better Serve Millennials in the Banking Industry
Published by Jessica Weisman-Pitts
Posted on July 22, 2022
5 min readLast updated: February 5, 2026
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Global Banking & Finance Review®
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Published by Jessica Weisman-Pitts
Posted on July 22, 2022
5 min readLast updated: February 5, 2026
Add as preferred source on GoogleGen Y’s Embrace of All Things Digital Is Forcing Banks to Accelerate Problem-Solving on Retention and Customer Satisfaction Using Speech AI and Data Analytics
Gen Y’s Embrace of All Things Digital Is Forcing Banks to Accelerate Problem-Solving on Retention and Customer Satisfaction Using Speech AI and Data Analytics
By Jonathan Cohen
Right brain. Left brain. Digital brain.
Forget the old ways of determining whether the dominant side of your brain makes you a creative free thinker (right) or analytical animal (left). Today’s problem-solving for enterprises increasingly focuses on the digital-brained customer – those with fingers flying across phone screens, who are more comfortable talking to a digital assistant over a person, and who harbor notions that stepping into a bank (or even having cash in their pockets) is quaint and outdated.
Millennials – the 25 year-old to 40 year-old cohort – are hitting their prime spending years. There’s 1.8 billion of them, representing 23% of the world’s population, and they’re not content with the status quo. They’re opening their digital wallets only for those companies they find to be most simpatico in industries such as personal finance, retail and automotive.
Banks in particular are high on their priority list. In a three-year study of Gen Yers published in 2013 called the Millennial Disruption Index, 71% of millennials said that they would rather go to the dentist than listen to what a bank has to tell them — a sentiment driven largely by poor customer service and poor technological integration. A third of those surveyed believed in the future they won’t need a bank at all.
While fintechs and technology players like Apple and Google are creating fast, easy-to-use mobile applications for customer interactions, incumbent banks have outdated legacy systems that make it more difficult to leverage the mountains of personal, financial and even social data they’ve amassed on each customer.
What’s more, many are missing the foundational voice assistant technology millennials are embracing in droves. Some 50 percent of 8,000 banking customers in a new CapGemini survey cited voice assistants as a feature they want to see most, yet only 35 percent of bank executives saw it as a priority.
To better compete, banks should embrace this prescription for technological change:
Some banks are rushing to adopt off-the-shelf technology from brands millennials know, including Amazon’s Alexa, Apple’s Siri and Google Assistant
Using metrics like 80% – 90% accuracy in understanding words, these seem like great solutions. That is, until you add words that are contextual only to a particular industry or age group. There, the word-error rate of non-customizable apps becomes useless if 80% of the contextual words return translation errors.
If humans have to take over the customer interaction because the software doesn’t understand key industry terms, chances are millennials, with their preference for fast and efficient service, will head for the exits.
Banks typically address the problem with customer service call centers and, increasingly, online chatbots. Yet these often fail to address their need for quick and easy resolution and support. Customers still are frustrated, for instance, that information given early in a callto the automated agent does not populate on the screen of the call center agent who comes on to handle more complicated tasks, forcing people to repeat everything from security data to the problem itself.
Improving customer service drives customer retention and lifetime value, while creating greater efficiencies in a significant cost center – banks globally are forecasted to save over $7.3 Billion via chatbots alone by 2023 according to Juniper Research.
Natural language processing can deliver AI-enabled applications beyond chatbots to drive even further productivity gains and customer service improvements. Coupled with an integrated sentiment analysis framework to track the customer mood from voice and text, agents can become more cost-effective if they can not only solve a problem based on a display of insights and trends but even cross-sell new services. For instance, a customer who received help transferring money into a deposit account for an upcoming vacation may value a recommendation to apply for the bank’s newest travel rewards credit card.
Young adults are increasingly looking for “super apps,” which tie multiple platforms or financial solutions into a pleasing interface using open APIs. Called open banking, the data sharing and AI tools enable banks to present customized content, cross-sell targeted products and present relevant third-party offers, such as sales on your favorite shopping sites.
To stay relevant, today’s banks will have to look very different, very soon. They’ll need to double down on mobile apps that are both technologically sophisticated, simple to use and safe from fraud. These apps will have to take a digital first approach, using computer vision for quick login, while delivering integrations with other personal finance, ecommerce, and investment platforms built to adapt as millennial preferences change.
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Jonathan Cohen is NVIDIA VP of Applied Research
Voice AI refers to artificial intelligence technology that allows users to interact with devices using voice commands, enhancing user experience in various applications, including banking.
Sentiment analytics is the use of natural language processing to analyze customer feedback and gauge their emotions, helping businesses improve customer satisfaction.
Hyper-personalization is a marketing strategy that uses data analysis and AI to deliver personalized experiences and recommendations to customers based on their preferences.
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