Credit Unions Can – and Should – Be Leveraging Machine Learning and AI to Bolster Member Engagement

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Credit unions’ personalized, human touch is arguably the largest of their many perks. Rather than being relegated to anonymity as customers depositing with an international bank might, credit union members enjoy a degree of familiarity with their local branch that’s otherwise hard to come by in contemporary banking.

This is made possible by credit unions’ most front-facing staff, the bankers who take it upon themselves to get to know their members and anticipate the respective needs of different accounts. As with any relationship, this is done through a trial-and-error process of learning what members respond to and how to best present solutions – this could take the form of asking candid questions, making small talk or trying to add levity to these interactions. Whatever the specifics, these exchanges help bankers learn more about what consumers are looking for in their individual banking experiences, what matters to them, and how to effectively draw connections between members’ needs and the ways credit unions can assist. Credit unions harness these dialogues to continually tailor how each member engages with them, and in turn, reaffirm the value proposition of storing money with them as opposed to alternative banking institutions.