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

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.

While the intimacy afforded by credit unions has given them a sharp competitive edge, it’s been somewhat dulled by the convenience of online banking. Although most U.S. consumers still bank with entities operating brick-and-mortar locations, many are depositing strictly through digital channels. As these services become more and more omnipresent, a growing number of consumers are only making in-person visits for consultations or to make deposits in the event their online banking resources aren’t functioning properly.

However, digital processes have yet to provide banks with the same relationship-building tools and benefits that come from direct, in-person consumer interactions. Despite the speed with which online banking allows users to check their balances, make deposits, open new accounts and more, it frequently leaves a lot to be desired when it comes to customization and specification. Credit unions excel at personalized banking, and as more users make the transition to digital-first financial services, there is an opportunity to bring that same degree of institutionalized member consideration to online offerings. Advances in technology have made it possible for credit unions to augment their human touch through digital means; rather than retreating behind the impersonal, one-size-fits-all interfaces that are pervasive in online banking, credit unions can both stand apart and increase membership by offering a customized experience underscoring the close attention extended to every account.

Though this may sound like a daunting task requiring ample web development, research and development, and funds for both, the fact remains that credit unions need to invest in themselves in order to keep pace with the future. As banking evolves alongside technology, credit unions don’t want to find themselves playing catch-up when they could be charting a course for innovation by leaning into their strongest qualities.

The capabilities underpinning the lofty promise of personalized online banking can be found in artificial intelligence and machine learning. As the availability and technological prowess of both has increased, companies utilizing these tools have gained deeper and more comprehensive insights into consumer behavior. Both AI and machine learning empower users to collect information on how consumers respond to particular marketing interactions or outreach efforts. Their flexibility also allows for exact adjustments to be made to the process, opening the door for more precise testing that details how consumers are deploying the service and how to optimize engagement with them.

For credit unions, the resources provided by AI and machine learning make it possible to tailor how members’ particular needs are addressed, as well as experiment with the most effective ways of gaining and retaining members through interactions. For example, there’s the requisite welcome sequence: While new members traditionally receive identical welcome emails upon joining a credit union, they don’t all take the same steps — whether it’s activating a debit card or depositing a certain amount of funds into an account — in exactly the same sequence. Using AI and machine learning, credit unions can dynamically generate onboarding sequences tailored to specific users based upon what is most relevant to them and beneficial to the overall relationship. Credit unions can also gauge the success rates of assorted outreach efforts and modify their usage accordingly. Further experiments could include testing out what kind of tone members respond best to in emails (e.g., formal and to the point versus endearing and personal), as well as evaluating what benefits or promotions most successfully spur users to deposit funds.

One of the most pronounced challenges of contemporary banking is resolving how to provide more digital empathy for users. While AI and machine learning can set up optimal conditions for engaging with customers and are dynamic enough to be adjusted for individualized needs or banking practices, credit unions are better suited than most banking entities to take full advantage of the technology’s potential in a manner that aligns with their core values. Because people pick credit unions for their promise of personalized banking, this technology stands to revolutionize the scale at which that takes place and bolster their core value proposition in the process. Looking to the future, the first credit unions to successfully migrate their services and institutional character to a customizable, digital-first experience, may well reinvigorate the health of the larger credit union ecosystem in the process.

Sarah Welch is the Managing Director and Head of Marketing Solutions at Curinos, a New York, N.Y.-based global data intelligence business serving financial institutions across lending, deposits and digital banking solutions.