Velera Builds Governance Framework to Shield Credit Unions From AI Risk

Watch more: Velera Builds Governance Framework, Shields Credit Unions From AI Risk

There’s no reason credit unions should be left out of the artificial intelligence conversation.

The technology is moving beyond theoretical discussions to become a tangible force transforming back-office operations, streamlining compliance and enhancing customer interactions throughout the financial services sector, and now at credit unions.

Economic uncertainty and fluctuating inflation are causing consumers and small businesses to face financial challenges. This environment underscores the role credit unions play in providing guidance and support, highlighting the increasing need for them to use technology — especially AI — to offer personalized assistance and improve financial wellness not just for individual members but also for corporate clients.

“AI is not magic,” Elizabeth Wadsworth, senior innovation strategist at Velera, told PYMNTS as part of the June “What’s Next in Payments” series focused on AI. “There are, of course, people behind the solutions on the back end.”

No matter the new products and services being shaped by credit unions and by Velera, as a credit union service organization, the emerging focus on AI governance and responsible AI remains essential for enabling tools like compliance monitoring. Wadsworth said that “there is a misconception that data governance and AI governance are the same thing, and that’s actually not true. They are actually two very different things.”

Streamlining the Back Office

In the “What’s Next in Payments: Secret Agent” discussion, Wadsworth described AI governance as comprehensive, encompassing aspects like strategy, alignment with organizational goals and identifying who within the credit union is qualified to manage these solutions.

Establishing this transparent governance framework up front, rather than waiting for regulators to inquire, is vital for navigating the regulatory environment, she said.

One immediate area where credit unions are harnessing AI is in improving behind-the-scenes operations. Tasks like preparing call reports, a process widely acknowledged as labor-intensive, are seen as particularly ripe for agentic AI applications.

Generative AI is being used for tasks like auto-summarization of calls in contact centers, allowing agents to grasp the essence of a member’s query. It also assists agents by auto-generating email drafts when responding to member inquiries. More advanced agentic AI applications, such as payment reminders or scheduling follow-ups, are on the horizon, Wadsworth said.

Building and Augmenting a Foundation of Trust

Enhancing the trusted relationship credit unions have with their members is paramount, she said. This trust is often built through frontline interactions, and AI can provide support.

One development seeing adoption is retrieval augmented generation (RAG). RAG involves creating a custom database for a credit union’s own information, such as policies. Frontline staff can access this system to quickly find answers to member questions or determine policy in specific situations, supplementing the personalized service credit unions are known for. In many cases, the member may not even be aware that RAG is being used; they simply receive the benefit of faster, more accurate service.

Using the vast amounts of data now available, including behavioral analytics, AI can help credit unions personalize interactions and offer assistance in real time. This is particularly relevant for financial wellness. AI solutions can provide budget insights by analyzing members’ spending habits.

Agentic solutions provide opportunities to build trust by giving the member agency, Wadsworth said. Instead of fully automating actions immediately, the system can propose actions and require member authorization. For instance, predictive overdraft protection could analyze spending and foresee a potential shortfall, then ask the member if they want to move money from savings to cover it.

Similarly, predictive analytics could identify that a member has a small amount of extra money in a paycheck and ask if they would like to use it toward paying down a loan. This optionality is crucial for cementing trust, making members feel looked after and strengthening the relationship through a two-way dialogue, she said. Over time, as trust is built, members may choose to automate these actions.

The benefits of AI also extend to credit unions’ commercial clients, particularly small businesses. Many small business owners operate as “one-stop shops,” managing numerous tasks themselves, making AI-powered tools especially helpful, she said. Two predominant applications are help with generating invoices and contract reviews. AI can take a contract and break it down into natural language, summarizing its contents.

Future agentic solutions in contract review could allow small businesses to input their typical negotiation parameters or rules they do not want to violate. AI could then analyze incoming contracts against these parameters, helping the business determine if a contract is a good fit and speeding up the review process. Agentic payment solutions could also allow small businesses to authorize vendor payments automatically once they are comfortable with the system’s accuracy, she said.

As the industry evolves, the emphasis on responsible AI frameworks will likely increase. Velera is partnering with the Responsible AI Institute to offer solutions for credit unions in this area, suggesting further developments are on the horizon.

As Wadsworth told PYMNTS, “the bedrock of all of this is going to be trust with the member — and building that trust takes time.”

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