Great Lakes Credit Union triples call containment rate to 75% with GenAI Voice Assistant
“Great Lakes Credit Union triples call containment rate to 75% with GenAI Voice Assistant” documents a Customer Service & Virtual Assistants deployment in Credit Union at Great Lakes Credit Union. interface.ai reports after-hours call containment rate: 75%; this directory has not independently verified that result.
Evidence at a glance
- Evidence status:
- Automated evidence gate passed
- Deployment timeframe:
- Not reported by source
- Reported outcome metrics:
- 3 cited below
- Directory entry published:
- Source link checked:
The source-link check confirms reachability, not independent re-verification of every claim.
Source-reported figures — cited source: interface.ai
The Challenge
Great Lakes Credit Union's legacy IVR system was underperforming by any measure — a 25% call containment rate meant three out of four callers still required a human agent, regardless of how routine their inquiry was. The system lacked contextual understanding and could not execute member-specific tasks like balance lookups or fund transfers. For a credit union committed to convenient, personalized member service around the clock, this created friction at every touchpoint: members encountered dead ends, agents were burdened with repetitive requests, and after-hours service quality suffered most. The status quo was eroding both member satisfaction and call center efficiency.
The Solution
In August 2023, GLCU deployed interface.ai's Generative AI Voice Assistant — named 'Olive' — marking an industry-first implementation of domain-specific GenAI voice banking. The assistant was integrated with Jack Henry Symitar, GLCU's core banking platform, enabling it to authenticate members and handle transactional requests including account balances, transaction history, and fund transfers — not merely informational queries. Simultaneously, interface.ai's Chat AI was deployed on GLCU's website to extend coverage across digital channels. The platform combines graph-grounded AI with generative capabilities built on over eight years of financial services domain intelligence, giving Olive the contextual fluency required to handle the breadth of credit union member inquiries across voice and chat.
Results
Call containment climbed from a baseline of 25% with the legacy IVR to 60% during business hours and 75% after hours — a threefold improvement driven largely by Olive's ability to complete transactional requests without agent handoff. Qualitative outcomes extended beyond call center metrics:
- Member satisfaction improved through accurate, context-aware responses available 24/7, replacing the repetition loops and dead ends of the prior system
- Agent roles shifted from transactional support to consultative, advisory work — resulting in higher pay grades and measurably better employee engagement
- GLCU's COO testified about these results at a U.S. Congressional hearing on AI Innovation in Financial Services, citing "remarkable results in terms of member satisfaction, call center performance, and employee engagement"
Key Takeaways
- Core banking integration is the critical enabler — without connecting to Jack Henry Symitar, Olive could only answer questions, not complete tasks. Task-completion is what drives containment rates above 50%.
- After-hours performance will outpace business-hours results; members with unmet needs outside staffed hours are the most receptive to self-service.
- Domain-specific AI outperforms generic voice solutions in financial services — 8+ years of credit union training data produced measurably higher accuracy and member acceptance.
- Frame AI deployment as a career-path upgrade for call center staff, not headcount reduction — GLCU's experience shows this framing improves change management outcomes and agent retention.
Explore Related
Details
- Industry
- Credit Union
- AI Technology
- Conversational AI & Virtual Assistants
- Company Size
- MidMarket
- Company
- Great Lakes Credit Union
- Evidence status
- Automated evidence gate passed
- Deployment timeframe
- Not reported by source
- Directory entry published
- Source link checked
Cited source
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