5 ways AI can improve customer service

Illustration by Idey/Adobe

AI can help solve customer pain points—but does it mean community banks will lose the personal touch they pride themselves on? As community bankers themselves tell us, the answer is no.

By Susan Springer

Quick Stat


The estimated amount of money banks will save by using AI applications by 2023.

Source: Business Insider

From gaming and online advertisements to autonomous vehicles and smart homes, artificial intelligence (AI) is used in a wide variety of ways. When it comes to banking, adoption is still in the early stages. However, when it’s thoughtfully applied to customer service, community banks can solve customer pain points and reap significant benefits—without losing the personal touch they’re known for.

How can AI accomplish this? First, with AI’s ability to mimic human intelligence, community banks can quickly process huge amounts of data to ease customer friction. Then, by monitoring AI as it works, banks can see where their customers’ experience can improve. That’s because AI iteratively improves itself based on the information it collects, with computer systems processing data and learning patterns through advanced algorithms.

“There’s incredible value in banks’ data, and they aren’t optimizing it either because of a lack of technology or it’s locked in the core. With AI, we can turn it into actionable insights.”
—Carson Lappetito, Sunwest Bank

Here are common issues customers experience that AI could improve.

“My accounts are scattered at different banks.”

“Many orphaned accounts sit inside community banks,” says Carson Lappetito, president of $2.5 billion-asset Sunwest Bank in Sandy, Utah.

Customers don’t want a fragmented banking relationship. “They often say, ‘You’re my core bank and I want my accounts together, I just didn’t know you had an SBA loan department,’” says Lappetito.

He believes community banks can easily improve their ability to cross-sell by using robust data analytics and AI to place the right products in front of the right customers. Partnering with vendor Neocova to identify cross-selling opportunities within Sunwest’s customer data was a game changer, he says. “We can see customers who are paying loans at other institutions, estimate loan balances and generate a shortlist by relationship manager,” says Lappetito.

Only a few months of targeted cross-selling has made a meaningful impact, increasing loan production and uncovering more deposit opportunities for customers. “It provided incredible fruits for us both in additional revenue opportunities and customer satisfaction.” While traditional cross-sell campaigns produced overload in the sales team, AI eased the process for all involved.

In addition, AI enabled Sunwest to pursue its specialty of solar lending. “Because the value in AI learning is a function of repetition, the more models and use cases, the more knowledge,” Lappetito says. Thanks to data sets beyond his own bank, the AI platform identified customers with large electric bills who would benefit from Sunwest’s solar expertise.

“There’s incredible value in banks’ data, and they aren’t optimizing it either because of a lack of technology or it’s locked in the core,” he says. “With AI, we can turn it into actionable insights.”

“It takes too long to get answers to simple questions.”

The pandemic meant fewer face-to-face opportunities for community banks. “They got creative quickly; the adoption of virtual assistants and chatbots spiked during COVID,” says Nicole Harper, director, corporate strategy at Jack Henry.

Chatbots, a software application that can conduct an online chat conversation via text, and digital virtual assistants (VAs) can give customers fast answers on their bank’s mobile app to routine questions such as, “What’s my balance?”

“Look at the top 20 reasons why they call, and you will identify the sweet spot of the high-volume, low-complexity things that create an opportunity to serve through AI,” says Harper.

She says community banks can tailor automation to their own customer service strategies. For example, a bank may feel comfortable allowing a VA to solve a login problem, while situations like a lost card are solved by an empathetic human. “Issues that create emotion are where you want to stand up and be the hero, since customers may have less appetite for automation,” Harper says.

“We want to balance providing the fast answers and solutions that customers are looking for without losing that personal touch.”
—Rory Bidinger, Stearns Bank

Some AI platforms can even detect emotion such as a raised voice, so that if an interaction moves beyond a simply query to frustration, the customer can be sent to an agent.

While chatbots or VAs are usually thought of as customer facing, there is also an agent assist model. “That can ensure your agent gets to the single right answer quickly,” Harper says.

“Did I get the loan or not?”

“We want to balance providing the fast answers and solutions that customers are looking for without losing that personal touch,” says Rory Bidinger, chief marketing officer of Stearns Bank N.A. in St. Cloud, Minn., adding that business customers may have high expectations of speed set by online lenders who can put them in touch with loans in a matter of minutes.

Stearns is still researching the expansion of AI operational functions, Bidinger says. Because the $2.3 billion-asset community bank prioritizes a personal connection with its customers and “commits that we will answer on the first ring,” it is considering how to provide convenience through AI while maintaining the human touch.

Stearns is exploring the use of AI for smaller business loans in its equipment finance division. As a national bank that serves customers in multiple states, Stearns makes loans and finance equipment for various industries, including medical, agriculture, construction and transportation. While AI can speed up answers to customers’ questions by automating credit reports, the community bank wants to understand and make loan decisions based on the whole customer—not just their credit score. A hybrid approach would enable customers to obtain funding faster while bankers maintained the customer relationship.

“We are trying to identify these types of opportunities where we can partner with other technology companies to provide services that our customers are looking for, instead of reinventing the wheel,” Bidinger says.

“It’s hard to reach a real human to help me.”

It’s no secret that the banking industry is one of many affected by the current staffing crisis, which has encouraged many banks to look for technology solutions. Some saw AI as the silver bullet.

“Customer experience has become a critical competitive advantage, requiring banks to completely change their approach to servicing customers,” says N. Venu Gopal, chairman of the board of Quinte Financial Technologies, Inc. “Today … people expect specialized services everywhere, all the time.”

AI can streamline processes significantly, freeing bankers’ time to interact with customers. For example, Gopal says there is a growing focus on automated lending. AI can be applied to capture credit information, perform some underwriting functions and present all relevant information, including analyst recommendations, on a single dashboard to lending staff to facilitate the decision-making process. With AI substantially improving operational efficiency in the back office, banks can reduce operational cost, errors and time required to process customer requests.

“We are seeing greater success in implementing AI to help with the automation of processes, which results in superior service and reduced turnaround time,” Gopal says. “We also see community banks striving to maintain that personal touch by empowering their staff through the use of AI.”

However, AI is not a set-it-and-forget-it solution, he says. “The systems do require constant supervision and review of outcomes to ensure that needs of the customer are consistently being met.”

“Paperwork takes way too long.”

“While AI could be applied to any layer in the tech stack, from back office, to customer facing, start with the back office including document processing, compliance verification and fraud detection,” says Sarah Hovde, head of investor relations at BankTech Ventures.

Hovde says banks need to clean up the back office first, so that customers don’t experience slowdowns due to bottlenecks in processing. If banks are driving more sales volume, they need the infrastructure to support that increased activity, or they’ll drown staff. AI can quickly manage repetitive, monotonous tasks. For example, tech can expedite showing a full view of a customer from a variety of platforms instead of a person working half a day to aggregate that same data.

“Leverage the technology to free up human capital by spending less time sorting through data,” says Hovde. “Then, move into the front office to improve customer service by offering more personalized products.”

Susan Springer is a writer in Oregon.

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