How Conversational Banking Can Improve CX and Lower Expenses

The banking industry has been quick to adopt artificial intelligence (AI)—and for good reason. In an industry with such a high number of customers and clients, tons of numbers to crunch, and the high risk of expensive errors, AI offers a way to work much more efficiently and accurately. 

Among the fastest growing use cases of AI in banking is conversational banking. Powered by AI and natural language processing (NLP), conversational banking helps create a seamless, personalized customer experience. The benefits of conversational banking goes far beyond faster response times—it drives operational efficiency, higher customer satisfaction, and gives banks a clear competitive advantage.

In this article, we’ll explore what conversational banking is, its benefits, how it improves banking metrics, and examples of how real banks are putting it into action.

What is conversational banking?

Conversational banking refers to the use of AI agents, like chatbots, to support customers with natural, human-like, and agentic conversations. These AI agents usually operate across a variety of channels, including online chatbots, SMS, voice, email, and more. 

Virtual banking assistants can help with: 

• Account inquiries like balances, rates, and personalized advice
• Loan questions, applications, updates, and payments
• Support needs like password resets, location searches, and routing numbers

Unlike traditional banking support, which can be slow and inconvenient, conversational banking isn’t bound by business hours, call volumes, or manual bottlenecks. 

Instead, it empowers banks to create self-service experiences that are immediate, personalized, and helpful. It can also significantly reduce costs by up to 20%.

Benefits of conversational banking

As AI gets more powerful, the use cases for conversational AI in banking are becoming more accessible, cost-effective, and efficient. Here are just a few of the benefits virtual assistants provide banks:

Customer retention and loyalty

Customers expect fast, personalized service, especially when dealing with their own money. Conversational banking gives financial institutions a powerful tool to meet rising expectations by offering 24/7 support, personalized recommendations, and proactive communication.

Capacity, a support automation platform, helps financial institutions meet customer expectations with a powerful mix of practical and generative AI. With omnichannel self-service, employee enablement, and automation tools all in one platform, Capacity can reduce operational costs by over 60%—while sending outbound campaigns or helping your team reach inbox zero.

Improved customer support and experience

In this day and age, we’re all constantly on the go. Conversational banking agents can support customers wherever they are—whether that’s online, on the phone, on a messaging app, on email, or on social media DMs. 

By giving customers the ability to contact support more easily, financial institutions can build trust and reliability. This level of convenience is even more impactful when all support channels are connected, meaning that users can start a conversation online and seamlessly continue it on the phone, without missing a beat.

These kinds of interactions are more human, more personalized, and more efficient, allowing banks to improve customer experience in a tangible way that leads to big gains in the long run.

Increased revenue and customer lifetime value

The more satisfied and engaged a customer is, the more likely they are to stick around, and in some cases, use more services. With conversational banking tools, financial institutions can personalize offers, upsell products, and nurture lasting customer relationships—boosting Customer Lifetime Value (CLV) in the process.

For example, a banking chatbot might suggest a credit card upgrade after analyzing a user’s spending habits, or recommend a savings account to a customer based on their financial goals. 

Personalization that feels timely and helpful can boost revenue by up to 25% according to McKinsey, making this a crucial investment for both improving conversion rates and reducing churn.

A competitive advantage

As more banks embrace digital transformation, conversational banking is quickly becoming table stakes. Institutions that lag behind in their technology offerings risk losing market share, not just to other banks but also to online banks and fintech startups, investment platforms, and other market disruptors.

Intelligent, connected AI agents can help banks catch consumer attention with more convenient, helpful, and personalized experiences. 

Reduced operating costs

Traditional banking processes are slow, manual, and time-consuming—not to mention costly.

But conversational banking can help. With banking chatbots there to intercept repetitive inquiries like password resets, support teams can focus on high-impact conversations

Importantly, these AI tools aren’t here to replace employees. Rather, they reallocate talent to where it’s most valuable. Banking chatbots handle the grunt work while human teams focus on complex inquiries that require empathy, problem-solving, and in-depth expertise.

This helps banks make the most of their human talent and work more productively and strategically, so they can drive real revenue rather than spend resources on low-impact activities.

From reactive to proactive

Relative to other industries, like retail or technology, banking has been more reactive vs. proactive. If a customer has a problem or a financial need, they reach out to their bank, and then wait for the bank’s response and support. 

With virtual banking assistants, banks can instead anticipate needs and address issues before they arise.For example, an AI assistant might notify a customer that they’re nearing an overdraft limit or offer help if unusual account activity is detected. 

AI agents can also execute outbound campaigns to help convert or upsell customer lists, giving customers additional financial options that feel relevant and timely.

With advanced, predictive analytics and automations, these AI banking agents can build trust while preventing churn.

Metrics conversational banking will directly impact

Conversational banking tools offer financial institutions real ROI—if they choose the right tool and strategy. Here are some key KPIs banks should keep in mind to improve while building an AI strategy:

Faster response times 

AI-powered banking chatbots can instantly respond to thousands of simultaneous inquiries 24/7, 265 days a year. They can support customers outside of business hours, on weekends, and on holidays—without hold times, interruptions, or delays.

This significantly improves both response times while reducing support expenses.

Time to resolution

Many customer inquiries are routine and repetitive. Answering the same questions over and over just isn’t a valuable use of time for human teams who should focus their expertise on higher-value work.

With virtual banking assistants, banks can deflect those FAQs while resolving them near-instantly. And for more complex inquiries, they can seamlessly escalate to human agents with full context.

For financial institutions looking to use generative AI in banking, tools like Answer Engine® offer a great opportunity: Answer Engine can retrieve relevant information following a simple prompt, allowing agents to improve resolution time even further.

Net promoter score (NPS)

Better service leads to happier customers—and higher NPS. This is important because NPS measures how likely a customer is to recommend a product or service, as well as how satisfied they are overall. 

Analyzing these scores can help banks improve their support experiences over time, especially as they implement AI agents. Improving this metric with tools like conversational AI can lead to word-of-mouth recommendations and online reviews as well as lower churn.

Internal knowledge access and agent efficiency

AI agents can’t handle every inquiry, and they’re also not just for customers. When an inquiry is escalated to a human agent, conversational AI can also help that agent serve the customer more quickly, accurately, and helpfully.

Tools like Capacity’s knowledge base and Answer Engine® equip support agents with instant answers to customer questions, as well as to their own: like internal policies or procedures.

This means that not only can agents improve their customer-facing metrics, they can onboard and train faster, produce fewer errors, and offer more consistent service. 

Plus, advanced automations—which execute processes across systems—streamline work for teams by eliminating busywork. 

👉 Learn more about financial automation use cases.

Fraud prevention

While not a direct support KPI, conversational AI banking tools can detect suspicious behavior and patterns by analyzing user behavior in real time. Combined with other fraud analytics tools, this can create a more secure, trustworthy banking environment that in turn improves metrics like customer satisfaction.

5 real-world examples of conversational banking

1. West Community Credit Union

WCCU is a not-for-profit, member-owned financial cooperative based in St. Louis. As a Capacity customer, WCCU leverages advanced conversational AI to offer fast, accurate answers to member questions. Their website chatbot answers over 90% of FAQs in just a few seconds, which not only improves member experiences, but also reduces the burden of answering repetitive questions on staff.

In fact, since using Capacity, WCCU has:

• Saved 20% in phone bill expenses
• Raised member growth rates by 7%
• Boosted growth in assets under management by 40%

All in all, WCCU is a prime example of how to use conversational AI in banking to improve customer loyalty while gaining significant ROI. 
👉 Want to learn more? Read the full customer story here!

2. JPMorganChase

As one of the largest financial institutions in the world, JPMorganChase has a lot of customers and partners to support. To reduce the burden on their support teams and maintain their reputation for stellar customer service, JPMorganChase uses AI agents for both B2B and B2C interactions.

They use two tools, COiN (Contract Intelligence) and Quest IndexGPT. Here’s how they work:

• COiN analyzes commercial loan agreements. Using a mix of NLP and machine learning, COiN can pull key information, find risk patterns, and significantly speed up processing time—eliminating 360,000 hours annually that were once spent reviewing these documents.
• Quest IndexGPT, on the other hand, focuses on individual investing experiences. Using OpenAI’s GPT-4 model, Quest IndexGPT builds guides for investors who want to pursue specific industries such as AI, e-sports, or renewable energy. This helps investors build stock portfolios much faster and in ways more suited to their own goals.

COiN and Quest IndexGPT are just a few of the AI banking tools that JPMorganChase uses to improve efficiency and experiences, and they’re already making a real difference in how people interact with the company.

3. BBVA México

BBVA México is the largest financial institution in Mexico, and also the first to implement conversational AI. To reach more customers and convert new ones, BBVA México implemented a conversational AI banking agent that integrates with WhatsApp.

BBVA México’s virtual banking assistant answer questions about:

• Branch locations and open times
• Opening and maintaining accounts
• Using the bank’s digital services and features

All on WhatsApp. Plus, because it’s integrated, the AI agent can assist over both chat and voice, increasing convenience and personalization.

As a result of its technology investment, BBVA México has completely differentiated itself and innovated its customer experience in a vast and crowded market.

4. Bank of America

Another influential U.S. bank, Bank of America’s Erica bot is a prime example of what conversational banking can do at scale. Available through the BofA app, Erica can handle bill payments, transaction alerts, budgeting tips, and more.

BofA implemented Erica in 2017 to reduce call volume into their contact centers. Since then, Erica has: 

• Completed over 2 billion interactions
• Helped over 42 million clients
• Boosted earnings by nearly 20%

Of course, with BofA’s prevalence in the market, matching these numbers may be difficult for smaller financial institutions. Still, the success of Erica goes to show that investing in conversational banking tools can pay big dividends.

5. HSBC

HSBC, a large financial institution based in the United Kingdom, also uses AI to improve customer experiences and lower costs. Specifically, they use generative AI in multiple ways:

• To assist servicing teams with over 3 million interactions, reducing turnaround times
• To streamline credit analysis by pulling data from key internal and external sources
• To enhance everyday productivity with translation and drafting assistance

HSBC is already integrating AI into core elements of their operations, making the entire banking process faster, more accurate, and more intuitive both internally and externally.

Final thoughts on conversational banking

Conversational banking is already helping financial institutions across the globe improve experiences and bottom lines. With AI-powered chatbots and virtual assistants, banks can boost customer satisfaction, lower operational costs, improve efficiency—and strategize for scale.

To succeed in a fast-growing market, financial institutions should use tools that prioritize delivering better support, deepening relationships, and empowering human teams.

That’s why Capacity is a great option: a support automation platform, Capacity powers all support activities with one knowledge orchestration layer, so banks can:

• Offer 24/7, omnichannel support across chat, SMS, voice, email, and social
• Empower teams to work smarter with instant knowledge access, automated QA, real-time suggestions, and more
• Automate repetitive work across teams and systems to streamline the day-to-day

Want to learn more about how Capacity’s conversational banking tools can help your institution? Request a demo today!

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