A colleague of mine recently attended the BankAI conference in Chicago. One of the most interesting presentations, according to him, involved a Midwestern credit union sharing details of its chatbot rollout fueled by the artificial intelligence (AI) tools of a fintech partner.
What set the story apart from the pack was the credit union’s size, a shade under $300 million in assets. It’s often assumed that AI projects are the domain of the largest financial institutions; certainly, their efforts gain the most attention. Bank of America continues to tout the mass adoption of its Erica virtual assistant, and Wells Fargo, Capital One and JPMorgan Chase have spearheaded high profile AI rollouts as well.
While it’s refreshing to see a grassroots project gain attention at BankAI, it’s far from the only example of AI being deployed beyond the Top 50 banks. The latest SRM Academy report outlines several areas where AI can deliver near-term benefits for institutions of all sizes. These use cases demonstrate why community banks and credit unions do not have to cede this tech-forward turf to their largest competitors.
Keeping Pace by Moving Forward
It also is important that community-size financial institutions understand the implementation of AI no longer represents an opportunity for competitive differentiation. The efficiency gains AI generates are rapidly becoming the baseline against which all institutions will be measured. Customer experience expectations have also been redefined, not only by tools like Erica but also the myriad of AI use cases that tech giants like Amazon have made part of the everyday life.
To date, banks and credit unions have shown themselves to be more comfortable initiating their AI journeys with back office applications. A $2 billion institution has found success processing travel notifications, ensuring that customers’ credit and debit cards are available for use when away from home. Another reports it has applied AI to the time consuming and often aggravating process of escheatment, improving accuracy and shifting key resources to more valuable endeavors.
Chatbots are a natural fit for customer-facing operations, such as call center optimization. One credit union reports a 50% reduction in the escalation of calls to second level support, with no drop in satisfaction. An institution with less than $200 million in assets has leveraged robotic process automation (RPA) to support the integration of two recent acquisitions. Management stated that it expects to reduce the cost of future mergers by as much as 80 percent, a potentially game-changing improvement given the continuing consolidation trend.
The Bottom Line: Think big, start small. The use of AI need not involve a full-scale operational overhaul; there are a host of isolated tasks and procedures where the technology can be applied, building expertise and organizational support for such endeavors. We expect AI to come out of the back office as banks and credit unions find value in updating consumer-facing processes. The lending process – specifically originations – is ripe for change in most organizations. Any enhancement that speeds the elapsed time from a potential borrower’s initial application to the receipt of funds, while diminishing the overall cost of the process, is certain to boost customer experience, create loyalty and improve ROI.
Our SRM Academy report offers further examples of areas where banks and credit unions of all sizes can apply AI to existing operations, avoiding the creation of gaps between large and small players while delivering faster service and lower cost with fewer errors.
