How to Use AI to Better Serve Millennials in Banking

Millennials’ adoption of all things digital is forcing banks to accelerate customer retention and satisfaction challenges using voice AI and data analytics

By Jonathan Cohen

Right brain. Left hemisphere of the brain. Digital brain.

Forget the old ways of determining whether the dominant side of your brain makes you a creative free thinker (right) or an analytical animal (left). Today’s problem solving for businesses increasingly focuses on the digital-brained customer – those whose fingers fly across phone screens, who are more comfortable talking to a digital assistant than to a person, and who have the idea that walking into a bank (or even having cash in their pockets) is quaint and outdated.

Millennials – the 25-40 year old cohort – are reaching their peak spending years. They are 1.8 billion, or 23% of the world’s population, and they are not satisfied with the status quo. They open their digital wallets only to companies they deem most sympathetic in industries such as personal finance, retail and automotive.

Banks in particular are high on their priority list. In a three-year Millennial Disruption Index study published in 2013, 71% of millennials said they’d rather go to the dentist than listen to what a bank has to say – a sentiment largely motivated by poor customer service. and poor technological integration. A third of respondents believe that in future they will no longer need a bank at all.

While fintechs and tech players like Apple and Google create fast, easy-to-use mobile apps for customer interactions, incumbent banks have outdated legacy systems that make it harder to mine mountains of personal data, financial and even social resources available to them. accrued on each customer.

Plus, many miss out on the fundamental voice assistant technology that millennials are adopting in droves. Some 50% of 8,000 bank customers surveyed in a new CapGemini survey cite voice assistants as a feature they most want to see, but only 35% of bank executives see it as a priority.

To be more competitive, banks should adopt this prescription for technological change:

  • Embrace Customizable Voice AI: This step is the basis of everything a bank could build after.

Some banks are rushing to adopt off-the-shelf tech from well-known millennial brands, 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 only contextual to a particular industry or age group. There, the word error rate of non-customizable apps becomes useless if 80% of contextual words return translation errors.

If humans have to take over customer interaction because the software doesn’t understand key industry terms, chances are that millennials, with their preference for fast and efficient service, will head to exits.

  • Surround yourself with Sentiment Analytics: The old joke that someone works a banker’s hours will rarely bring a smile to the face of a millennial looking for 24/7 customer service. Used to constant connectivity and smartphones, they are more likely to laugh at 9-5 banking hours (closed on public holidays and Sundays).

Banks typically address the issue with customer service call centers and, increasingly, online chatbots. Yet these often fail to meet their need for quick and easy resolution and assistance. Customers are always frustrated, for example, that the information provided at the start of a call to the automated agent does not show up on the screen of the call center agent who handles more complex tasks , forcing people to repeat everything from security data to the problem itself. .

Improved customer service drives customer retention and lifetime value, while creating greater efficiencies in a major cost center – banks worldwide are expected 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 more productivity gains and customer service improvements. Coupled with a built-in sentiment analysis framework to track customer mood from voice and text, agents can become more profitable if they can not only solve a problem based on a display of information and trends, but even sell new services. For example, a customer who received help transferring money to a deposit account for an upcoming vacation might appreciate a recommendation to apply for the bank’s newest travel rewards credit card.

  • Sharpen your hyper-personalization: Once upon a time, hyper-customization was considered nice to have. For millennials and next-gen Zers, slow adoption in this area could spell doom in the long run.

Young adults are increasingly looking for “great apps,” which combine multiple financial platforms or solutions into a nice interface using open APIs. Called open banking, the data-sharing and artificial intelligence tools enable banks to showcase personalized content, 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 will need to double down on mobile apps that are both technologically sophisticated, simple to use and safe from fraud. These apps will need to take a digital-first approach, using computer vision for quick connection, while offering integrations with other personal finance, e-commerce and investing platforms designed to adapt to the evolving Generation Y preferences.

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jonathan Cohen is NVIDIA VP of Applied Research

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