This month, we’re debuting a new format: to counter the glut of information bankers face every day, going forward we’re going to focus on three headline statistics that tell a story in banking every month. Expect the same level of expertise from the Narmi team – now formatted to make deep insights stand out.
Is there anything that bankers haven’t heard about the promises of AI? Aside from the usual rhetoric around resource efficiency, new narratives around how AI will rework the customer relationship are beginning to emerge. But how do we make these ideas less theoretical and create a framework around them that banks and credit unions can follow?
It starts with listening to customers. This month we’re focusing on some of the most critical relationships any community financial institution has – small-and-medium businesses (SMBs) – and how they feel AI plays into their unique needs in this economic environment.
Some encouraging research findings for AI-optimists: an overwhelming majority of SMBs using AI reported measurable efficiency improvements after implementation. The data, included in a recent conversation Narmi Group Product Manager Yaro Melnyk conducted with The Financial Brand, follows from expectations about initial engagements with AI. When it comes to the most obvious AI use cases to start with (IT, customer service, marketing initiatives), SMBs are finding that the results are as promised – less time dedicated to administrative tedium, and more time for the core value-adding functions that help SMBs compete in their markets.
“The most innovative SMBs are realizing the value of these tools and moving quickly to use them across their organizations,” said Melnyk. “As the underlying models become more powerful, AI enabled SMBs will see an outsize benefit compared to less nimble organizations.”
It’s clear that SMBs are currently in an experimental phase when it comes to AI, making small, organic tweaks to their workflows and seeing what works in the absence of enterprise mandates to completely revolutionize the way they work. Whether “fully AI-enabled” will materialize for SMBs is yet to be seen. But the data proves that at the very least, financial institutions should be prepared for more incremental uptake from SMBs, with momentum developing over time.
This tends to work in financial institutions’ favor: under significant regulatory oversight to safeguard users’ banking data, financial institutions tend to be more incremental in adopting AI as well. In SMBs, they’ve found a subset of customers/members willing to match their pace, giving both entities the opportunity to test different use cases, broaden their integrations, and curate the reliability of LLMs.
“The more data it has access to, the more powerful it is,” said Melnyk. “When financial institutions support integrations with ERPs and other financial tools, they create a richer environment for analysis.”
That’s not to say that financial institutions don’t have an opportunity here: recent polling from Goldman Sachs report similar findings in terms of the positive impact of AI and lack of full integration into operations. It also surfaces another area of focus – one of the main barriers to wider adoption is a lack of AI fluency and implementation resources within small businesses.
Financial institutions should see this as the basis of a new form of relationship cultivation with SMBs. Strong relationships are where community banks and credit unions stand out – SMBs’ outstanding questions about AI are an opportunity to cultivate those relationships. Financial institutions should take the lead in adopting AI functionality and providing education/best practices for SMBs looking for this guidance, turning a straightforward transactional relationship into something closer to a consultative approach.
“Financial institutions have an opportunity to show their clients that they shouldn’t be intimidated or afraid of these tools, that they’re already helping you combat fraud and they can help you with more.”
