Banks and credit unions are sitting on an underleveraged growth asset.  

For years, the banking contact center has been measured almost entirely on efficiency with key metrics including handle time, first-call resolution, and cost per interaction. The primary goal was to manage a high volume of inbound service requests, and the technology available in past years did not offer much beyond that. 

Now AI is handling a growing share of routine banking inquiries, including balance checks, transaction disputes, and basic account changes. In turn, this frees up agent’s time and capacity considerably.  

The question banks and credit unions are beginning to ask is how to redirect that capacity toward growing relationships with the customers who are already calling in. 

What has held banking contact centers back 

It is no secret that a frontline job in a banking contact center is a difficult one. Agents are often early in their careers and manage a high volume of complex interactions in a regulatory environment. 

They are expected to resolve customer issues quickly and accurately while staying current on products, policies, and compliance requirements that change regularly. 

Asking these agents to identify and act on sales opportunities, without a clear framework, compliance guardrails, and confidence in their own product knowledge, has held back the service-to-sales motion.  

Agents who are not given the right tools will default to what feels safest, which often means pushing the product they are most comfortable with or responding only to what the customer asked for. 

Three structural barriers have driven that dynamic in banking: 

1. The metrics trap: Agents are evaluated on handle time and call volume, metrics that reward getting off the phone quickly. Without a framework that makes product conversations efficient and measurable, agents have no incentive to have them.
2. The knowledge gap: Banking products are complex, and the details are important to get right. Without tools that surface the right information at the right moment, agents are left to fill that gap on their own, and many will default to staying in their comfort zone rather than risk saying something wrong in front of a customer. 
3. The confidence and compliance problem: Banking is one of the most regulated industries and the fear of a misstep around product disclosures, fair lending, or suitability creates an understandable habit of avoidance. Without guardrails that make compliant conversations feel safe, the personal downside of initiating a sales conversation outweighs the upside for most agents. 

Why now is the right time for banks to act 

McKinsey research indicates that financial institutions can improve top-line revenue using service-to-sales strategies by 10% to 20% while simultaneously reducing service costs by 5% to 10%. 

Within the contact center itself, sales performance already varies by 230% between top and bottom performers. Equipping every agent to rise to the level of the best performers can result in significant gains in revenue.  

AI is making that gap easier to close than ever. As automated systems handle more of the transactional volume, branch and contact center staff are being freed from more repetitive and tedious tasks. Institutions that redirect that capacity toward deepening customer relationships and agent confidence to pitch suitable options have a market advantage. 

How leading banks are turning inbound service calls into revenue opportunities 

Banking contact center agents handle hundreds of inbound calls from customers checking balances, disputing fees, asking about their mortgage, or managing their accounts on a daily basis. Unlike cold calls, these are conversations with customers, people who are already engaged with your institution. However in many institutions, when the issue is resolved, the interaction ends there. 

Handled well, the inbound service interaction becomes the starting point to deepen relationships with customers. A customer calling about a fee reversal may also be a candidate for a premium checking account. A customer asking about their savings balance might be ready to hear about a higher-yield product or a CD.  

From service call to sales conversation 

Start with context: Knowing your customer 

When an agent picks up a call without visibility into who the customer is, what products they already hold, and what they might need next, the interaction starts at a disadvantage. Connecting customer data such as account history, profitability tier, and prior service interactions to the agent’s workspace before the conversation begins is a huge enhancement. 

With that context in place, a customer calling about a common inquiry such as a fee reversal can receive an immediate resolution. Their satisfaction remains the priority throughout, and a new product conversation is complementary to their needs. 

Matching the right product to the right customer 

It is not that agents are unwilling to have product conversations, but rather they do not know which product to bring up, or how to get there naturally. A guided discovery approach changes that by prompting agents with structured questions that identify customer needs and adapt based on the customer’s responses. 

A credit union using this approach saw agents uncover two additional product opportunities — a balance transfer and a savings account — from a single credit card application conversation that would otherwise have ended at fulfillment. 

Looking ahead

The banking contact center has long been viewed through the lens of cost management. What the data and early results show is that the same operation, equipped with the right tools, can become one of the most direct and personal channels a bank has for growing customer relationships. 

The barriers that have prevented this in the past such as compliance risk and a lack of product knowledge can be mediated with today’s tools. AI does not replace the agent’s judgment or the human quality of the interaction but gives agents the context, confidence, and guidance they need. 

This can be achieved with:   

• Real-time customer data to personalize each interaction, drawing on account history, profitability tier, and next-best-action recommendations.  

• Guided sales playbooks that surface needs-identifying questions automatically, so agents always know what to ask next instead of improvising.  

• Post-resolution product offers triggered by next-best-action logic at the moment customer goodwill is highest.  

• Compliance guardrails that reduce the risk of agent error to near zero, giving frontline staff the confidence to have product conversations without fear of misstepping.  

 

One financial institution saw a 30% lift in credit card sales after A/B testing eGain’s Sales Advisor against their existing approach. Leadership had prioritized credit cards, a high-margin product category, where agents had historically underperformed relative to deposit products. 

If your institution is exploring how to turn inbound service volume into a revenue channel, eGain offers a readiness assessment that evaluates where you stand today and outlines a practical path forward. 

Frequently Asked Questions 

Can a bank’s contact center realistically be used as a sales channel?  

Yes. When an agent resolves a customer’s issue well, that customer is at their most receptive. With the right tools and guidance in place, that moment becomes a natural opening to introduce a relevant product without the interaction feeling like a sales call. 

What are the biggest challenges banks face when trying to drive sales through the contact center?  

The three most common barriers are agent incentives, compliance risk, and product knowledge. Agents are rewarded for speed, not conversations. In a regulated environment, saying nothing feels safer than saying the wrong thing. And without the right tools, most agents do not feel confident enough to engage. 

How does AI help banking contact center agents have better sales conversations?  

AI removes the guesswork by surfacing customer context before the call, prompting agents with structured questions that adapt in real time, and matching responses to the most suitable product. It gives agents a guided path rather than asking them to improvise. 

How do banks keep sales conversations in the contact center compliant?  

By building compliance guardrails directly into the agent workflow. When agents are guided through approved language and prompted with required disclosures at the right moment, the risk of error drops significantly and the compliant path becomes the easiest one to follow. 

What kind of results can banks expect from a contact center revenue strategy? 

McKinsey projects 10% to 20% top-line revenue improvement alongside a 5% to 10% reduction in service costs. In practice, results vary by starting point, but the 230% performance gap between top and bottom-performing agents signals significant headroom for most institutions. 

Where should a bank start if it wants to turn its contact center into a revenue channel? 

Start with an honest assessment of how agents are currently measured, what playbook and product knowledge infrastructure exists, and where the gaps are. From there, the path involves aligning incentives, building guided conversation frameworks, and putting the right data and compliance tools in place.