Can AI’s impact in the bank boost human significance?

In preparing our range of articles for our BAI Executive Report: Harnessing the power of AI in banking, a few takeaways remain with me. First, that AI is already, or soon will be, impacting nearly every department of a financial institution, its staff and its customers to varying degrees. And second, the experts tapped for this issue to a person see a pivotal future role for human gatekeepers and growing demand for higher skills among personnel as AI reshapes financial services.

Caution around AI is legitimate and well-advised, but to deny that it is a game-changer could put banks and credit unions at a serious disadvantage. AI, automation and other digital efficiencies empower bankers to be more strategic, create time to engage more fully with the communities they serve, and to more accurately measure performance and trigger operational pivots in real time. Ignoring the benefits of these technologies could impact recruitment and employee satisfaction over the long run.

The unique duality of an AI and human partnership in banking is apparent in our report’s lead feature, which asks “Can AI give financial advice?” To answer that question, I interviewed Brian Gunn, who helps run an AI-powered personal finance platform that links with banks. Gunn stresses that he sees AI as a “co-pilot” for the banking professional. And he reminds us throughout the piece to only ever consider AI as a tool. Gunn strongly believes in human responsibility in deciding how and when that tool is used.

As he puts it, “Financial decisions often involve complex considerations and emotional factors best navigated with the guidance of a human advisor. The ideal scenario is one where AI augments the expertise of a human advisor, providing data-driven insights to offer more-informed recommendations. But the human remains the gatekeeper.”

Gunn also advanced my thinking about AI with another acronym. He targets Retrieval Augmented Generation, or RAG, as a growth area for AI in financial advice and financial management. It’s an advanced technique in natural language processing and it notably draws from up-to-date, contextually appropriate responses, according to Gunn, “resulting in highly accurate and relevant answers to financial inquiries.” Please dig into this interview for his ideas on how RAG and generative AI will continue to grow in personal finance.

Insight from Alkami’s Marla Pieton this month reinforces what Gunn believes. Pieton sees considerable scope at financial institutions to leverage predictive AI modeling to, for instance, regain the confidence of wavering customers when their behavior flags that they might jump ship. Predictive AI can also be used to capitalize on cross-selling possibilities. But Pieton especially emphasizes growing expectations among younger customers for how and how fast banks and credit unions provide service. Meeting this demand, says Pieton, can eventually only rely on the power of AI. In fact, younger generations already or soon enough will come to expect that their financial institution is enhancing their experience with AI.

An Alkami report uncovers that among demographic groups, Millennials are the most comfortable with AI usage in banking, with 51% agreeing that AI can improve their digital banking experience. They are particularly open to AI’s role in financial wellness and personalized banking solutions. Please read Pieton’s full article for her take on how all generations feel about AI and banking.

BAI partners asked for content addressing the potential for AI as banks and credit unions integrate diversity, equity and inclusion (DEI) within their organizations. We were curious as well. Our second feature shows that for human resource and recruitment departments, as well as any staff who make DEI a priority, it’s the scale of AI that changes the math. AI can easily analyze huge databases to identify and monitor noncompliance with DEI standards. Banking staff can ask AI to suggest ways to be more inclusive of ideas coming from employees and prospects whose backgrounds differ from theirs and extend those practices to job postings.

As I mentioned at the top, I’m especially pleased with the range of AI topics, number of impacted banking departments and selection of operational use cases that our issue covers. Within, you’ll also find industry knowledge on:

• AI engagement from small and medium-sized business (SMB) owners. This includes how the banks and credit unions who’ve made SMBs a valuable customer target should heed these signals. Shruti Patel, chief product officer for business banking at U.S. Bank, says solutions might include AI-powered financial planning and financial management for the business and for staff retirement, API-based interfaces into accounting systems and integrated treasury management solutions.
• AI’s role in making the lending process more efficient. Moody’s Anand Thirunellai Radhakrishnan says AI allows banks and credit unions to be more precise with financial analysis and maintaining credit quality, which lowers potential unexpected risks. An AI-backed streamlined process not only likely speeds up loan applications and decisioning end to end but can sync functions like credit memo formatting and covenant management. Making more efficient use of resources, Radhakrishnan argues, satisfies customers and staff alike.
• The benefits of AI-enforced fraud prevention, especially for smaller institutions. Eric Tran-Le at NICE Actimize believes that AI is not a luxury, rather a necessity for smaller FIs that want to stay competitive in an increasingly digital banking environment. Fraud prevention powered by always-on AI offers real-time detection, operational efficiency, an adaptable defense against evolving fraud methods and improved customer trust, he writes.
• Embracing AI as the key that unlocks out-of-reach data. According to MeridianLink’s Devesh Khare, emerging natural language and conversational tools enable banks to interact with their data like never before. Instead of relying on static reports and dashboards, bank leaders are now engaging in real-time conversations with their data, asking complex questions and receiving immediate, data-driven insights for faster, more informed decision-making.
• Allowing AI to transform contact centers for the benefit of customers and agents. AI in the call center improves the customer experience and helps staff deliver, which goes a long way to boosting performance and avoiding burnout. Vericast’s Steve Hasmanis believes AI isn’t going to replace your contact center. It’s going to enhance it. In fact, he says, contact centers that combine the best of AI and human interaction will be the ones that deliver superior customer experiences and drive lasting business success.

I’m all for thinking about AI with an open mind, especially a future that includes the power of people and the latest that automation has to offer.

Rachel Koning Beals is Senior Editor with BAI.