2025 Chatbots in Banking: Benefits, Use Cases, and Best Practices

A banking chatbot acts as a virtual customer service representative that handles customer queries in real-time without delays. According to a report, over 110.9 million users are projected to use the bank's chatbot by 2026. This shows the promising and rapid growth of financial chatbots.

In this guide, we will uncover all about chatbots in banking, including its benefits, use cases, how-to steps, and much more. But first, let's understand the banking industry's challenges.

Main Challenges of the Banking Industry

The banking industry is in the middle of a digital revolution. Rapidly advancing technologies, changing customer expectations, and growing competition present many challenges to the banking industry.

Some of the main challenges banks face that highlight the need for chatbots are as follows:

• The Demand for Digital Services: Customers expect more digital services to access instant banking services.
• High Operational Costs: Traditional banking practices involve more humans, manual processes, and outdated systems, which often lead to operational inefficiencies and higher costs.
• Fintech Disruption: An increasing number of fintech companies are impacting the businesses of the traditional banking industry and urging banks to offer faster and cheaper solutions.
• Regulatory Compliance: The banks have to deal with a growing number of new regulations.
• Cybercrimes: With digitalization, cyber threats and cybercrimes are also increasing and becoming challenging to tackle.
• Technological Advancement: The rapid pace of technological advancements offer both opportunities and challenges. Banks need to leverage technology advancements to remain competitive and offer the best service experience. At the same time, they have to ensure that these integrations don't disrupt operations and lead to security loopholes.

In short, the banking industry is undergoing a radical shift, which is bringing new competition and challenges for them.

However, a few right moves can make a big difference. For instance, the use of chatbots in banking can offer personalized, digital services to customers, lower operational costs, improve competitiveness, and much more.

So, let's shift our focus on conversational AI for banking and how chatbots are the game-changer for banks.

What are Chatbots in Banking?

Chatbots in banking, or banking chatbots, are software solutions that provide personalized digital assistance to customers. They use natural language processing (NLP) and machine learning to engage with customers in human-like conversations and give answers to their queries that a human agent answers otherwise.

With conversational AI in banking, customers get a virtual customer support representative that is available 24/7 across different digital channels and can answer account-related questions or general queries, like account balances, loan inquiries, and more. In addition, the chatbot can also send proactive notifications about activities or important updates.

The key use cases of banking chatbots include:

• Automate basic banking activities
• Answer FAQs
• Troubleshoot issues
• Send reminders
• Recommend products
• Provide insights and analytics

In short, chatbots in banking can help automate common customer queries, give customers digitalized services, and lower operational costs.

How Does Banking Chatbots Work?

The working principle of banking chatbots revolves around using natural language processing and machine learning algorithms to understand and respond to customer inquiries.

A customer can engage with a chatbot through a website or any other accessible platform and ask questions, like:

• What is my current balance?
• How do I apply for a credit card?
• I want to apply for a mortgage.

The chatbot will interpret the question and look into its pre-trained data to find the most relevant response. It can also fetch real-time data from the bank's database, like the current account balance. Afterward, the chatbot gives the exact response.

Conversational AI chatbots for banking can continue back-and-forth conversations with customers until their issue is resolved. They can also direct the query to a human agent on the customer request. Moreover, they also keep learning from customer responses and improve their accuracy with time.

Benefits of Financial Chatbots

A conversational AI in finance brings many benefits, from customer satisfaction to operational efficiency and more. Here are some key benefits of integrating financial chatbots:

Personalized Experience

71% of customers want businesses to offer personalized interactions. Chatbots are the way to offer customers the personalized experience they expect.

A chatbot can respond to customers as they want, which increases their satisfaction. For example, if one customer wants to check the balance while the other customer wants to get a product recommendation, the chatbot can facilitate them accordingly.

24/7 Availability

Banking chatbots do not sleep or need rest. They are operational 24/7 and ready to serve customers any time of the day. Customers can engage with the chatbot at 2 am at night and get the assistance they need. This responsive customer service is what customers want from banks in today's era.

Self-Service

Chatbots in banking give customers self-service capabilities. Using the bot, customers can get account information, update profile information, and manage other activities. Simply put, self-service can help customers solve many issues without visiting the branch or calling any representative.

Operational Efficiency

Chatbots can handle FAQs and other common issues that human agents must tackle otherwise. This means a bank can automate the response to common queries and enable human agents to focus on more complex matters. Secondly, it also reduces the need for having a large human support team and in-house resources. All these attributes lead to operational efficiency and cost savings.

Upsell and Cross-sell Strategies

Banks offer customers a wide range of financial products, whether it is account types, investment options, loans, or credit cards. So, one of the benefits of AI in banking is that chatbots can include upsell and cross-sell strategies. A chatbot can analyze a customer's transaction history and spending habits and can recommend financial products accordingly.

Analytics for Better Customer Understanding

Chatbots in banking are more than problem-solvers. They can also offer useful analytics. They record and analyze all the interactions they have with customers and then provide useful analytics and reports. Based on that, a bank can make data-driven decisions. For example, a chatbot may highlight that many users are facing errors while accessing internet banking. So, the bank can work on fixing the issue.

Examples of Chatbots in Banking

Many banks are already actively using chatbots to give customers a digitalized support experience. So, let's list out a few financial chatbots that are currently available:

Example 1# Erica by Bank of America

Bank of America offers Erica, a conversational AI for banking that helps customers handle many banking activities on their own. They can use the chatbot to check balances, paying bills, transferring funds, getting spending insights, and more.

Example 2# Amy by HSBC

Amy is a banking chatbot by HSBC that can help ask FAQs, provide account balances, and more. It can also find nearby ATM locations and provide data about bank products/services.

Example 3# Eno by Capital One

Capital One also offers a similar conversational AI in finance called Eno. This chatbot can check account balances, provide previous transaction records, pay bills, and do much more.

How to Build a Banking Chatbot?

Building chatbots in banking is not rocket science. There are now easy-to-use chatbot builders that can help you create a full-fledged chatbot without coding. One such best chatbot builder in GPTBots.

GPTBots is a no-code AI bot platform to build business chatbots. It provides a visual builder to customize the chatbot flow without coding. It is trainable with your bank data with a simple upload process. Moreover, it can integrate large language models with the bank's data and services to offer customers real-time access to banking.

All the above features of GPTBots help financial organizations leverage the benefits of AI in banking. In fact, GPTBots conversational AI chatbot can resolve up to 95% of customer support issues and increase leads by 300%.

Feel impressed? Check out the below steps to learn how to build chatbots in banking with GPTBots:

Step 1. Go to the GPTBots.ai website and sign up. From the main dashboard, click "New Bot" and start from blank or use a pre-designed template.

Step 2. Customize the bot settings, like finalizing the large language model (LLM), response length, etc. In the "Identity Prompt", explain the bot's roles, skills, and other details.

Step 3. Next, you should train the bot with the knowledge base. To do so, click Knowledge > Documents and upload the corporate data from PDF, spreadsheets, website URLs, and more. The tool will intelligently extract useful insights.

Step 4. After training the bot, go to the "Debug" mode and test its performance.

Step 5. Once you have finalized the chatbot, go to Integrations and integrate the chatbot into your preferred platforms. For example, if you want to integrate on the website, you can use the Bubble Widget integration option.

In this way, you can easily create financial chatbots with the no-code approach of GPTBots.

Best Practices for Banking Chatbot

Today, 61% of customers interact with banks on digital channels weekly. When a bank integrates a chatbot, it can boost customer engagement and satisfaction. However, it is equally important to offer the best chatbot experience to customers.

In this perspective, below are a few best practices that can optimize your use of conversational AI in banking:

Aligned with Customer Needs

Conversational AI for banking is only effective when it aligns with your customer needs. Before building a chatbot, you should know what your customers want. Do they want 24/7 support, self-service capabilities, or others? Based on that, you should build a chatbot that aligns with their needs.

Robust Security and Compliance

Chatbots handle sensitive customer data and transactions. Therefore, it is important to put extra emphasis on security and compliance with rules and regulations. Some of the best practices include multi-factor authentication, secure messaging channels, adherence to GDPR, and more.

Seamless Integration with Existing Bank's Systems

Chatbots need to access bank databases to fulfill banking activities. This means they have to be properly integrated with bank's systems, such as CRM, account management, or transaction processing systems.

Omnichannel Support

Build a chatbot that can facilitate omnichannel support, i.e., it can integrate with all the communication platforms customers can use, such as websites, WhatsApp, Telegram, and others. The omnichannel support provides convenience to customers to interact with the bank from their preferred channel.

Regular Update

Chatbots in banking is not a one-time thing. You need to update the bot with new information and functionalities as per the changing customer demands and market dynamics. Therefore, regularly update the bot and keep it relevant for customers.

Conclusion

Chatbots in banking are becoming an emerging way to access a bank's customer service. They can streamline operations, enhance customer experience, and help banks drive digital transformation to remain competitive. Therefore, it's time to take the first step and modernize the banking services and enhance customer engagement. Try out GPTBots and create your own financial chatbots.