AI adoption has been steadily increasing across the finance industry. Recent insights show that 72% of finance leaders are using AI in their operations.

Banks and other financial institutions have been turning to AI to streamline operations, speed up resolution times, strengthen digital services for customers, and more. McKinsey reports that generative AI alone could provide a massive $340 billion a year in additional value for the banking industry.

For credit unions, however, it’s a different story. While they stand to benefit from AI solutions in similar ways to banks—addressing operational gaps, ensuring stronger account handling, and more accurate loan approvals—credit unions are ‘losing ground’ in the digital space.

Credit unions have lagged behind in digitalizing their processes, and it makes growth hard. Operational inefficiencies continue to plague credit unions, leading to frustrated members, damaged reputations, burned-out staff, security risks, and error-riddled account information. Because of that, they’re also missing out on connecting with younger, digitally-savvy account holders.

These issues have got to be tackled head-on, and AI is at the forefront of helping credit unions do that. Otherwise, they’re not just putting their assets on the line, but their member relationships, too.

Failing to keep pace with younger generations 

Credit unions struggle to attract younger members. As a result, their share of new account openings has dropped in recent years.

While the most wealth sits with Baby Boomers, credit unions can’t ignore the preferences and behaviors of younger demographics. Millennials, who are widely dubbed ‘digitally native,’ are currently the U.S.’s largest living adult generation. Although Baby Boomers currently make up the largest portion of credit unions’ customer base, their wealth will soon be transferred to younger inheritors.

The Great Wealth Transfer—set to be the largest amount of wealth passed between generations—is looming on the horizon. Over $100 trillion is expected to be inherited by Generation X, Millennials, and Gen Z, mainly from Baby Boomers, in the next two decades.

Right now, gaps in credit unions’ operations are painfully evident. Members are having poor experiences due to a lack of a self-serve option when handling their accounts, inheritance, or estates.

Inefficiencies are also pervasive. Every interaction, document, and step is manually reviewed and actioned offline. It’s common to hear stories of wanting to deposit money and finding it difficult to do so online. This is eating up huge amounts of time among countless members and employees.

These issues are exacerbating deposit losses across credit unions. Handling inheritance claims is a convoluted, confusing, and cumbersome process. Due to traditional offline inheritance processes, inheritors often have to endure countless phone calls and office visits, speaking to a different person every time. They’re chasing after important information that should be available to them in one click and one space.

If credit unions keep failing to digitize their services in line with younger generations’ expectations, they will endure even more massive leaks of deposits, especially from inheritance. Consumers are much less forgiving regarding brand experience: 51% have indicated that they would be less loyal to a company if the online experience is less enjoyable than in-person.

Modernizing tech stacks and providing streamlined, instantaneous, and accessible member experiences is therefore a non-negotiable amid the Great Wealth Transfer.

Throwing people at the problem 

Credit unions are throwing people at the problem when they should ultimately be doing more with less. On top of that, 75% of credit unions are operating on legacy loan origination systems.

Outdated legacy infrastructure continues to be a major barrier to automation among credit unions. These legacy systems undermine underwriting processes and lead to significant issues, like erroneous rejections of loan applications. This compounds the operational strain on staff who then have to step in and rectify the situation. That’s precious human resources lost that would be far better spent nurturing member experiences and relationships in other ways.

Another issue is that outdated systems tend to be fragmented, which is a serious impediment to seamless automation and secure data exchange. Fragmented systems and data silos go hand in hand. Credit unions are guaranteeing mishandled accounts because of inaccurate or missing data, ruining member experiences and jeopardizing their loyalty. It’s not surprising that so many inheritors, who tend to come from younger generations, end up closing their accounts and leaving.

Fragmented systems also prevent further technical innovation. It’s significantly more difficult for credit unions to modernize their digital ecosystem if they’re trying to navigate apps and systems that aren’t connected or compatible.

Not only does that prevent members from accessing a unified experience, but it can put credit unions at serious risk of security breaches. AI solutions have now been developed to help credit unions monitor security measures, notifying them of potential breaches or anomalies.

However, these solutions can only work when they’re interoperable within a credit union’s tech stack. Poor interoperability leads to misinformed AI that produces incorrect outputs and fails to fulfill automation needs.

Underestimating integration challenges

Successful AI integration doesn’t happen overnight. Neither should AI be blindly adopted at every member touch point or step in a process. It takes careful planning and assessing business and operational needs.

First, credit unions should pinpoint where exactly AI makes sense in their existing operational processes. Mapping out business and operational needs is key to implementing a robust AI strategy. It also helps to gauge member needs and pain points. This helps credit unions uncover the most pressing issues that AI can help resolve.

Next is not to lose sight of the human touch where it’s most needed. That tends to be situations where there’s a lot at stake or emotions are running high. Distressed account holders won’t want to deal with a bot, but will want a helping human hand. Instead, integrate AI into highly repetitive or simple processes, like addressing basic queries that can be answered with FAQ-like responses. To reiterate, employing AI at certain touch points of the customer journey can be incredibly helpful, but the overall human presence should be available, too.

Data also must be addressed when integrating any form of AI. Shockingly, though, 80% of financial institutions cite data as a significant hurdle to effectively leveraging their data assets. For AI tools to work optimally, credit unions must ensure their data is sound. Key steps include:

• Cleaning data to remove any anomalies, errors, and duplicates.
• Implementing a data governance framework for compliance, security, and accountability purposes. This involves embedding auditing trails for complete visibility around data sources and destinations.
• Ensuring that data is well structured and interoperable between platforms and tools to prevent AI hallucinations and bias.

Finally, trust must be preserved when introducing AI, not just for members but for staff, too. That means maintaining transparency around AI integration and compliance with relevant regulations. The teams who will be working with these tools, and the members whose experience will be shaped by them, will want reassurance that AI is not a threat to their privacy and experience in any way.

Implementing a communications strategy that prioritizes transparency and reassurance around the reliability of adopted AI tools is recommended. It can also be reassuring to explain the rationale behind AI adoption in the first place, particularly to wary staff who may be resistant to embracing the technology. Hands-on training in the form of workshops is important here so staff not only understand how AI technologies work, but also how to oversee them.

Be open with your members

Trust is the bottom line of any strong customer relationship, and credit unions can’t compromise on that. Ensuring traceability, accountability, and compliance—and clearly communicating that these are being upheld—is crucial to strengthening universal buy-in to AI.

It’s not a matter of if, but when, credit unions start adopting AI into their digital blueprints en masse. Avoiding these mistakes and knowing what makes the foundations of a robust digitalization strategy will help credit unions navigate the coming years, including the Great Wealth Transfer.