Banking Chatbots in 2025: 15 Tools, Use Cases & Practices

Banking chatbots help customers complete transactions with ease using voice or text. Chatbots can reduce operational costs and improve customer satisfaction by streamlining interactions.

Banking bots are an emerging technology, and banks are advised to test their solution robustly before deployment to ensure that their reputation is not harmed by chatbot glitches.

See top banking chatbots with their features like no-code UI and pricing, what banking chatbots are, their benefits to banks and customers, and how you can build functional banking chatbots:

Top 15 chatbots in banking

Features

Ranking: Sponsors (products with links) are at the top. The rest are organized in an alphabetical order.

Inclusion criteria: 20+ reviews on B2B review platforms.

Pricing & plans explained

*As the number of conversations increases, the fee in the growth plan also increases.

Table features:

• The table details the pricing plans offered by the above vendors to their customers and the contents of the plans. Each upgrade means all the features of the previous plan + the features in the table. Therefore, in each plan, we give the distinguishing features from the other plans.
• Apart from our sponsor, Freshchat, the table is organized in an alphabetical order.
• The decrease in the number of vendors in this table is due to the fact that 6 products from the above table do not clearly share their pricing policy.

What is a banking chatbot?

Banking chatbot, also called conversational banking (commerce), is the new era of digital service offering. In this era, AI driven virtual financial assistants, perceives and executes the banking transactions of customers. They can also provide opportunities to automate the relationship between the consumer and the bank. 

From the historical point of view, digitization of banks began with ATMs and then telephone banking. Evolution process has been followed by online and mobile banking, and now we are in the era of conversational commerce (see Figure 1).

We owe the advancements in conversational AI and rising mobile usage-apps to the conversational finance era. Since banking chatbots are becoming more sophisticated, which goes hand in hand with their popularity.

Why are banking chatbots important now?

Automation provided by chatbots will be beneficial for banks:

• Chatbots are cost-efficient. Accenture research shows that 57% of companies agree that chatbots can result in large returns on investment with minimal effort.
• Demand for mobile banking is increasing across all age demographics. 24/7 available chatbots integrated to mobile applications can offer users immediate solutions to their urgent problems that they can not resolve via the app.
• Customers prefer messaging. Almost all mobile users are familiar with messaging apps such as Whatsapp, Telegram, Slack. Written and conversational communication over those applications is preferred especially by millennials. Banks are also testing using these popular messaging platforms for customer service.

Top 4 use cases of banking chatbots

1. Lead generation and qualification

Chatbots can engage with the visitors on the bank’s digital platforms to generate leads and assess those leads with relevant questions.

Example: After a customer completes a transaction on a bank’s mobile app, the chatbot initiates a brief conversation asking for feedback. Instead of filling out a long survey, the customer answers a few questions conversationally, making the feedback process more engaging and less time-consuming.

2. Customer service

24/7 availability, and the tireless and consistent nature of chatbots for customer support is an important advantage for chatbots in banking. 

3. Feedback Collection

Long feedback forms and surveys can be a nuisance to complete. A chatbot can engage customers with its natural language understanding and generation.

Example: After a customer completes a transaction on a bank’s mobile app, the chatbot initiates a brief conversation asking for feedback. Instead of filling out a long survey, the customer answers a few questions conversationally, making the feedback process more engaging and less time-consuming.

4. Personalized marketing strategies

Customers’ conversations with chatbots can be analyzed to personalize the bank’s messages for the customer.

Example: A customer frequently interacts with a bank’s chatbot, asking about mortgage rates. The bank analyzes these conversations and sends personalized emails with information on mortgage products, rates, and offers that match the customer’s interests.

Top 5 banking chatbot best practices

1. Understand the limitations and challenges of chatbot technology

A good analysis of the capabilities and limitations of existing AI-powered chatbot technology can set the right expectations and goals.

For instance, during the initial phase of implementation, you conduct an analysis to identify areas where the chatbot might struggle, such as understanding complex queries or handling sensitive transactions. This helps set realistic expectations and goals for the chatbot’s performance.

2. Review how to protect user data

Banking companies are responsible for protecting the information gathered by chatbots. Data security must be reliable for the chatbot. Since data leaks can harm a company’s brand and finances. To enhance your cybersecurity posture, you can read our cybersecurity best practices article.

GDPR is a good example: a banking company should make sure that its chatbot complies with data protection regulations like it (Figure 2) You should encrypt all customer interactions and regularly audit the chatbot’s data handling processes to prevent leaks. This protects customer information and maintains the bank’s reputation.

3. Review how to secure transactions

Chatbots, especially those that focus on customer service, increase the attack surface. The transactions that they can complete, authentication procedures etc. need to be reviewed to ensure secure service.

A chatbot can assist with money transfers and bill payments. The bank reviews and strengthens its authentication procedures, such as using two-factor authentication, to ensure these transactions are secure. This minimizes the risk of fraud and unauthorized access.

4. Build specialized chatbots

There are many use cases of banking chatbots from lead generation to customer service. Starting with a domain specific chatbot can simplify requirements which is critical in any technology project.

For instance, you may want to start with a chatbot specifically designed for handling credit card inquiries. This specialized chatbot can manage tasks such as checking balances, making payments, and reporting lost cards, simplifying the development process.

5. Test extensively

There are numerous cases of chatbot failure. Do not let your financial institutions’ conversational agent be a failure. Testing for edge cases can help minimize or prevent screenworthy failures of your company’s chatbot.

So, before launching its new chatbot, you should conduct extensive testing, including edge cases such as unusual customer queries or high transaction volumes. This rigorous testing helps identify potential issues and ensures the chatbot operates smoothly, preventing failures that could affect customer trust.

FAQ

For more on chatbots

For more on chatbots and AI in financial services, feel free to read these articles:

• Digital Transformation for Banking: In-Depth Guide
• Chatbots: In-depth Conversational Bots Guide
• 30+ Chatbot Usecases/Applications in Business

Finally, if you believe your business would benefit from adopting a chatbot platform, we have a data-driven list of vendors prepared. We will help you choose the best one for your business: