Historically, regional banks and credit unions have built their brands through personal relationships with their account holders. For example, it wasn’t unusual for you to know the name of your teller’s spouse and for them to know your kids’ names. Indeed, personal relationships have been the hallmark of smaller financial institutions and what has set them apart from their larger competitors. The digitization of banking has made forging personal relationships a challenge, eroding the differentiator and leaving smaller institutions searching for a way to reset the board.
Enter generative artificial intelligence (GenAI), which is a subset of AI technologies that uses large language models (LLMs) to learn patterns from large datasets. It then uses the patterns with prompts and directions from a human to create new text content that resembles or enhances original, human-generated work.
The 2025 Retail Banking Trends and Priorities report we sponsored this year found that 80% of organizations believe digital agents will rely on generative AI for real-time personalized marketing communications by 2030 and 76% of financial institutions believe that most financial institutions will be using GenAI by 2030. We actually believe the percentage should be higher, given that GenAI can substantially increase productivity, support better data-driven human decision-making, help deliver improved and more personalized digital customer experiences, and boost the bottom line significantly.
How significantly? At the end of 2023, The McKinsey Global Institute estimated that, among industries globally, GenAI could add the equivalent of $2.6 trillion to $4.4 trillion annually in value across the 63 use cases it analyzed. Among industry sectors, banking is expected to have one of the largest opportunities, with the potential to deliver between $200 and $340 billion in new value to retail banking — largely from increased productivity.
Faster, Better, Happier
There’s a misconception that AI will take jobs from humans. But the power of GenAI is that it produces content based on data and information plus prompts and directions given by humans. It’s an enhancement tool, not a replacement tool.
Currently, GenAI in banking is mostly used to automate critical but repetitive tasks or processes, including security, loan origination, fraud detection, and to deliver better automated service experiences. Allowing GenAI to take over the mundane work associated with these and other processes not only increases efficiency and productivity, it also frees up the employees doing that work to focus on more meaningful assignments, thus making their jobs more satisfying.
One of the primary ways regional banks and credit unions can differentiate themselves is by personalizing and elevating the digital banking experience of account holders. Specifically, the technology facilitates deeper insights into their behavior and predilections to help anticipate their needs. So, products and services that meet those needs can be offered to them in the same way Netflix offers its customers curated entertainment, and Amazon offers its customers entertainment and products — based on customer behavior and preferences.
Similarly, the data gathering and deep analysis possible with GenAI enables the creation of personalized content, so each account holder will see only content (including marketing campaigns) relevant to them at a certain time in their life. It makes no sense for a middle-aged woman who owns her own home and has a good salary and credit score to see the same content as a recent college graduate who’s trying to pay off student loans and still aspires to own a home.
The Human Touch
The inclusion of human decision-making and oversight are critical to building GenAI solutions for banking. Our formula for successful integration of GenAI is to start with deep learning models trained specifically on large banking datasets. These models, which have also been trained to learn the patterns and structures of human language, then create natural responses to user queries or prompts. Human involvement is crucial to ensure that AI-generated responses are accurate and align with ethical standards, regulatory compliance and customer needs — while mitigating potential risks and biases.
Tomorrow’s Tech, Today
The potential of GenAI to transform regional banks and credit unions is unbounded. The financial institutions that succeed in integrating the technology will be those that start strategizing for the future while focusing investments on high-potential and lower-risk applications, today.
Here are four primary ways we see GenAI making immediate and substantial impacts in the service of banking.
Driving strategic growth
The McKinsey report calculated that corporate and retail banking will benefit the most from the correct deployment of GenAI. On the corporate banking side, the highest potential is enhanced human-in-the-loop decision-making, automated risk assessment models and operational efficiencies through automation. Retail banking stands to benefit from personalized banking experiences, improved customer service and marketing innovations.
Powering operational efficiency
In a report on the top banking trends for 2023, Accenture identified banking as the industry most likely to be thoroughly impacted by GenAI and the industry with the greatest potential to increase output with the technology, with 34% of current workflows ripe for GenAI enhancement. It also found that financial institutions that adopt GenAI can improve their productivity by up to 30%.
But even with the potential for GenAI to improve efficiency, human expertise remains the key to success. Using specific banking knowledge, internal teams can train the models to be accurate and to assess complexities the way humans can. But they can scale faster and to a level far beyond human capacity.
Leveling the playing field between larger and smaller institutions
We’ve seen a few of the ways GenAI can benefit regional banks and credit unions, including increasing productivity and enabling personalized account holder experiences. It’s a positive sign that notoriously risk-averse bankers are recognizing the myriad benefits of GenAI, with adoption rates rising, but we still see too many regional financial institutions hesitant to jump on board.
While they dawdle, the big financial institutions are on the move. And they are only skimming the surface in leveraging the power of GenAI. Those who continue to be overly cautious will be permanently left behind. The thing to remember is GenAI tools can be ring-fenced, connected to proprietary data and kept internally.
Delivering collective intelligence
Collective intelligence is created when individuals and groups work together. Components may include group decision-making, consensus formation, ideation from different sources and motivation from competition. Traditionally, leveraging collective intelligence was done by documenting institutional knowledge and sharing it through training and job experience. GenAI elevates the benefits of collective intelligence — easily and in real time.
The successful adoption and increasing integration of GenAI in regional financial institutions will require LLMs specifically trained on banking data and deep industry knowledge. But the crucial element is human collaboration and oversight. Remember, GenAI is an enhancement tool, not a replacement tool.