With nearly 75 million Americans speaking languages other than English at home, it’s no surprise why credit unions are making the shift to improve accessibility for non-English speakers. But for some institutions, ensuring non-English-speaking members get the same experience their English-speaking ones do is a massive hurdle, and many don’t know where to start, or if the effort is even worth it.

It is.

When a credit union incorporates more language options into branch services, it’s not just about capturing an untapped market (although that is helpful). It’s about building trustworthy, transparent relationships with members and their families, and fostering financial stability, education, and loyalty in their communities. Credit unions who do this effectively are shown to have an increase in member growth, account openings, and fewer abandoned accounts overall.

To start, most people tend to prefer getting new information in their native language. Educational materials and courses presented in languages other than English can help immigrant communities better understand their rights and protections under the banking system and avoid scams in the future.

But language accessibility doesn’t just extend to people who sign up in Spanish—it affects English-speaking members too. A bilingual member may have opened their account in English but would prefer their statements in Spanish. Or a family looking to buy a home might feel more comfortable discussing mortgage options in their native language but are willing to sign a contract in English. The ability for a credit union to cater to their members’ preferences is what builds trust, and when it comes to member experience, the benefits of this fluidity show in lasting member relationships and more account activity.

AI becomes an excellent tool for filling in any gaps a credit union may have with their member experience, especially if that credit union is working with limited time, resources, and staff.

In situations where bilingual staff is especially limited, implementing real-time translation and interpretation software becomes a lifesaver for bilingual employees, who often end up playing multiple roles throughout the day. For example, a credit union with only one NMLS-certified Spanish-speaking employee will face difficulties closing mortgages and loan applications when that employee is also helping tellers, loan officers, and financial counselors with Spanish-speaking members.

However, many credit unions have amazing member experiences in their branches and contact centers, run by talented bilingual staff. What can AI do here?

For starters, take a look in the back office. Does the credit union offer courses and educational materials in other languages? What about marketing initiatives and lending products? Is the member experience consistent in every branch, or just a few?

Plus, Spanish isn’t the only other language in the US: languages like Chinese, Korean, Arabic and Haitian are often overlooked when searching for bilingual hires, and even a credit union with the strongest Spanish member experience can’t always replicate that experience in Vietnamese. To help all employees (including bilingual ones) serve members that speak languages other than English and Spanish, AI becomes an indispensable tool.

With AI covering these gaps, a credit union’s marketing department can develop promotional materials that actually resonate with their diverse communities; the financial education team can expand their efforts to include communities often overlooked and underserved. The operations team doesn’t have to worry about lapses in coverage when a bilingual employee leaves or gets promoted. Instead, they can focus on bringing in quality hires who speak a variety of languages.

Before implementing anything, it’s also important to note that AI is not meant to replace bilingual employees or prevent new employees from getting hired. The goal is to facilitate human connections as often as possible.

For credit union professionals starting to familiarize themselves with AI translation and interpretation, getting started doesn’t necessarily involve big, sweeping changes, either. Working one step at a time can ensure AI gets incorporated into the credit union properly, plus it gives employees time to familiarize themselves with the new technology. A few steps to improving language accessibility in a credit union’s member experience could include:

By starting small and focusing on member needs, credit unions can incorporate AI into their member experience strategy in a way that feels like an intentional step forward, instead of simply jumping on the AI bandwagon.

To do so, a thorough analysis of how members interact with the credit union, what products they use, and the problems they encounter are in order. How can your credit union start to fill gaps in your member experience, and what would you need to make it happen?