University Federal Credit Union (UFCU) in Austin, Texas, has revolutionized member satisfaction and operational efficiency through the strategic integration of AI and machine learning technologies.
By addressing critical pain points such as reducing check-hold times and enhancing fraud prevention, UFCU has not only improved the member experience but also streamlined internal processes.
“UFCU is very focused on our members, and we do that in different ways, including research about the consumers that we're serving and the community that we are in,” said Esther Edevold, UFCU's Vice President of Insights and Innovation. “This helps drive the credit union’s mission of helping people and understanding who the people are that we're trying to help."
During the pandemic, UFCU identified a significant issue: members were willing to wait in long drive-through lines to deposit checks with tellers, avoiding automated methods such as ATMs due to frequent check holds.
Data revealed that 40% of automated deposits were placed on hold, compared to a much lower percentage for in-branch and drive-through deposits. Members who discovered this were willing to wait in line to avoid the possibility of a check hold.
To tackle this problem, UFCU utilized data analytics and developed machine learning models to understand member behavior and risk factors. The initial solution increased funds availability and reduced call volume by approximately 40%.
“We created a model that balanced the risk of a check being returned against the reward of providing members quicker access to their funds,” Edevold said. “This significantly reduced the wait times and improved overall member satisfaction."
UFCU has also employed AI to enhance fraud prevention. Predictive fraud solutions help flag unusual member behavior, potentially stopping fraud before it occurs.
The credit union’s AI models allow UFCU to identify and prevent fraudulent activities more effectively. They review these models monthly to ensure they remain unbiased and ethical.
UFCU plans to leverage AI further to automate reconciliations, improve data analysis, and identify strategic opportunities. This will include dynamic transaction limits, automated underwriting rules, and predictive modeling to identify member challenges.
UFCU recently activated an in-house knowledge base that allows contact center reps and branch team members to find accurate answers quickly, Edevold said. It consolidates company information that previously had been spread over numerous servers and locations. This greatly improves the chance that answers provided to members’ specific questions would be the same across the organization, regardless of department or location.
Edevold emphasized the importance of overcoming fears related to AI: "I would say that you're not going to lose your job to AI, but you could lose your job to someone who's leveraging AI. If you're not leveraging AI, then you're going to not be relevant at some point, and so you have to get past that fear.”
UFCU's commitment to innovation and member satisfaction is evident in its strategic use of AI and machine learning. By addressing pain points, enhancing fraud prevention, and streamlining internal processes, UFCU sets a powerful example for other credit unions. As AI technology continues to evolve, UFCU remains dedicated to providing exceptional service and support to its members.
