Why Routing Members is Costing You More Than You Think

For CX leaders at banking institutions and credit unions, the challenge of managing service quality while controlling costs is a delicate balance. While institutions build a reputation for personalized, high-touch service, a silent friction in the digital channels may be undermining that effort.

Imagine a member calling their bank with a straightforward request such as activating a new debit card, or checking the status of a loan application, or disputing a transaction that looks unfamiliar. They verify their identity and explain the crisis to the automation system - only for the system to be routed to live support. When the human agent joins in, the first question is almost always the same - “How can I help you today?”

At that moment the member realizes that the last three minutes were wasted. They are forced to re-verify themselves and reconstruct the context that the automation layer was supposed to capture. While this experience may just seem like a minor annoyance, the operational impact is significant.

Why Continuity Matters in Credit Union and Regional Bank Member Experience?

Credit unions and regional banks differentiate themselves through service that feels personal as compared to big banks. And, when a member is forced to repeat themselves, it isn’t just a service gap—it’s a drain on the two most valuable resources: member trust and the operational budget.

This friction creates a cascade of hidden costs:

• Eroded Member Trust: When members have to repeat their request multiple times, the experience begins to feel inefficient and impersonal, which runs counter to the service model that most credit unions and regional banks work hard to maintain. McKinsey research shows that members dissatisfied with their institution's digital channels are 2X more likely to switch to a competitor.
• Increase in Average Handling Time (AHT) as conversations restart after each transfer. Over thousands of monthly transfers, this AHT Leak not only scales into hundreds of wasted hours, but lower first contact resolutions because the automation layer is unable to address the request.
• Staff Burnout & Talent Drain: When digital tools can only route inquiries, live agents are buried in routine low-value tasks instead of deepening relationships. This drives up turnover and prevents teams from doing the high-value advocacy work they were hired for.

These operational drains from bloated call times to staff frustration aren't the result of poor training or a lack of effort. They are the direct consequence of a technology architecture that was built to move work around rather than actually completing it.

Why Legacy Automation Fails to Move Beyond Routing to Live Support?

The operational costs aren't accidental; they are the result of a major architectural flaw in traditional automation. Most legacy tools in financial services were originally designed with a simple objective: classify requests and route them to the correct department. The technology stack typically follows a predictable pattern. A chatbot or voice assistant identifies the member’s intent, determines which queue should handle the request, and transfers the interaction to an agent.

This design made sense when the primary goal was to reduce menu navigation or shorten the path to the right department. Over time, however, the limitations of this architecture have become more visible.

• Rigid, Decision Tree-based Automation relies on an inflexible, "if-this-then-that" script. It works fine if a member follows the path perfectly, but the moment a member asks a follow-up question or changes the subject, the system breaks. This lack of flexibility forces an unnecessary transfer, even for tasks the bot was technically programmed to handle.
• The Inability to Take Action: While the automation can tell a member their balance or show a transaction, it lacks the connection to your banking core needed to actually perform actions. Because it can’t update an account or process a request, it has no choice but to hand the work off to a human.
• Disconnected Data at Handoff: Most automated systems only pass on basic metadata such as the detected intent or the queue assignment to the live agents. The full conversational history, authentication steps, and intermediate responses are often lost or difficult to access in real time as human support environments often operate independently. The result is a conversation that starts from scratch.

A Different Approach: Automation That Resolves Requests

A growing number of financial institutions are beginning to rethink this model. At Level AI, we believe the goal of automation shouldn't be to deflect a member, but to resolve their request.

Resolution-first automation changes the role of the virtual agent. Rather than acting as a digital receptionist, the system becomes capable of completing specific tasks on behalf of the member. This shift from routing-only to resolution-first approach is made possible by three key capabilities:

• Autonomous Actions: The primary reason most automation fails is that it can only look up information, not act on it. Level AI changes this by integrating directly with your core banking systems like Symitar or Fiserv. Our platform helps you resolve customer inquiries autonomously by performing real-time actions that are policy-driven - whether it’s a travel notice, a fee waiver, card activations or more.
• Human-Quality AI to power Natural Conversations: Level AI uses reasoning capabilities to understand a member’s intent, even if they change the subject or ask a clarifying question mid-process. Because the AI is anchored to your institution’s specific business policies, it provides the same high-quality, compliant guidance as your best-trained agents. This allows the system to follow the member’s lead without hitting a dead end or forcing an unnecessary transfer.
• Strategic Human-AI Balance: Unlike competitors who focus solely on maximal automation at the cost of your brand, Level AI focuses on the harmony between your human and AI teams. We connect the bot and the human team in one system, creating a Human-AI Intelligence Loop. Level AI provides the live agent with a conversation transcript, the authentication status, and the actions that have already been attempted. This ensures that the agent never has to ask, “How can I help you today?” and the customers never have to repeat their story.

Explore a Resolution-First Model for Credit Unions and Regional Banks

Many credit unions and regional banks initially adopt automation to reduce call volume or streamline digital channels. Over time they discover that routing-based systems often introduce new friction rather than eliminating it. And, by moving beyond basic routing to embrace a resolution-first approach is when their contact center stops being a cost to be managed and starts becoming a driver of customer loyalty.

By bridging the gap between your digital tools and your human experts, you achieve more than just a lower AHT. You create a Human-AI Intelligence Loop where your best agents’ expertise constantly improves your AI, and your AI handles the routine tasks that used to cause staff burnout. This strategic balance allows your team to focus on what they do best: advocate for your members and deepen the relationships that big banks simply cannot replicate.

With a 5-week speed-to-value implementation, the transition from a fragmented journey to a unified, high-resolution experience is closer than you think. It’s time to stop just routing your customers and start giving them the answers they need, the first time they ask.

If you are evaluating how AI can support member service without sacrificing trust or operational discipline, you can explore how this approach works in practice!