How AI helps financial services modernize operations and drive member satisfaction

Credit unions today must navigate a rapidly evolving financial landscape where members expect personalized, high-quality service. Yet, many are constrained by aging infrastructure and manual processes that limit their ability to modernize the customer experience. As a result, financial services leaders are increasingly recognizing the impact AI-powered CX software can have on their ability to understand their customers and provide smooth customer experiences.

In fact, The Economist Intelligence Unit found four in 10 financial services firms are already using AI for this purpose, and a NVIDIA study found 51% of leaders strongly agree that AI will be important to their company’s future success. This was the case for Oregon-based Maps Credit Union (Maps CU), which turned to NICE to modernize its contact center operations, elevate service across its departments and drive efficiency. With NICE’s integrated platform, Maps CU was able to dramatically improve call handling efficiency, member satisfaction and overall operational performance.

How Maps CU modernized its contact center

Maps CU has been serving its community for more than 75 years. The not-for-profit credit union’s teams take the company mission— “Every Member Benefits”—seriously, orienting operations around the goal of improving the financial position of all members. As part of that, its contact center and electronic services teams are always striving for efficiency as they help members achieve their financial goals.

Before adopting NICE, however, Maps CU’s contact center faced numerous challenges due to outdated technology that hampered its ability to deliver optimal service. Limitations included an inadequate telephony infrastructure, a lack of call recording and inefficient post-call processes. These issues prevented supervisors from conducting thorough quality reviews, limiting their ability to identify and act on opportunities to improve member satisfaction and service delivery.

Maps CU turned to the NICE platform, deploying Interaction Analytics (IA) to drive business outcomes from all member interactions, Enlighten AI for CSAT to uncover objective insights on agent behaviors that influence customer satisfaction on every interaction, and Enlighten AutoSummary to enable fast, accurate generative AI-powered summaries for every interaction. The integrated CXone Mpower platform also brought together the powerful features included in Interaction Recording, Quality Management, and Feedback Management solutions.

Results: Improved efficiency and member satisfaction

The impact of the new AI-driven tools was immediate and profound for the credit union. Interaction Analytics provided real-time insights into potential fraud and enabled better staffing decisions, while Enlighten AI for CSAT gave agents immediate feedback on their performance, ensuring consistent service delivery. AutoSummary reduced the need for manual notetaking, reducing average handle time and after-call work.

“AutoSummary was a game changer in that it has drastically reduced after call work time from 2 to 3 minutes per call down to 20 to 30 seconds,” said Michelle Seymour, VP of Contact Center and E-Services at Maps CU. “Agents just think it's the coolest thing they've seen, because it's amazingly accurate. If your organization is requiring your agents to manually note in any way, this is a hundred percent a no-brainer.”

Other results included:

• A 21.6% increase in handled calls per agent per hour
• Over 4,000 calls per month resolved via IVR or self-service
• A 4% reduction in call abandonment rates

The Feedback Management module helped Maps turn member feedback into actionable insights, directly aligning it with operational improvements. For example, members expressed confusion regarding queue position and wait times, which led to targeted adjustments in IVR scripts. These improvements led to a noticeable boost in customer satisfaction, reflected by consistently higher CSAT scores.

Maps CU’s success underscores the value of AI to drive both efficiency and member satisfaction. By combining interaction analytics, insights into member interactions and agent behaviors with automated interaction summaries, organizations can elevate both member experience and operational efficiency. Read the Maps CU case study to learn more about how the financial institution revamped contact center operations to fuel long-term performance and efficiency gains.