Conversational AI For Banking: Use Cases, Examples, And Benefits

In 2023, the market for conversational AI products was valued at $9,9 billion. It’s estimated that by 2032, it will rise to $57,2 billion, with a CAGR exceeding 21,5% between 2024 and 2032. Adopting conversational AI tools in e-commerce, retail, manufacturing, and real estate has seen significant growth in recent years.

While the banking sector is behind, it has found many applications for chatbots and virtual assistants. Institutions in this field successfully work with conversational AI stools, saving resources and hours of work. According to the latest data, 88% of banking executives believe in the role of these products as a significant communication channel. Our article is all about the use of these solutions in the banking sector, their top examples, and their benefits.

Current Examples Of Сonversational AI In Banking

Implementing AI systems in a sphere as complicated as banking is a process not all institutions find affordable. Several American banks have the time and resources to integrate conversational AI products into their daily work successfully: American Express, Bank Of America, Capital One, and JPMorgan Chase. Currently, financial institutions use several types of conversational products:

Chatbots

These tools work as intelligent banking assistants that answer common questions and help with financial management. AI-based chatbots send alerts and notifications, offer account balance information, and work as personal helpers to bank customers.

Financial Advisors

Banks use advanced financial helpers to offer investment advice based on clients' preferences. This type of conversational AI for banking makes economic predictions. With financial advisors, customers evaluate risks and explore ideas for stock investments.

Voice Assistants

These solutions let bank clients access various financial services with their voices. Such assistants work like advisors and chatbots, activated using voice commands. They provide information about loans and paying credit card bills.

Here’s how America’s top banks utilize conversational AI to improve their work:

• American Express. This institution has a Facebook Messenger chatbot, Amex. The tool uses conversational AI for financial information such as purchase history, account balance, and spending habits. American Express assistant tells about credit card benefits and sends recommendations and sale notifications.
• Bank Of America. The bank has Erica — a chat-based assistant. The solution delivers notifications, updates the FICO score, and tells clients how to save money and make bill payments. 
• Capital One. Clients of this bank have access to an assistant called Eno. This tool offers tips on different money-saving strategies to its customers. Eno also helps bolster account security and track spending.
• JPMorganChase. America’s largest bank’s chatbot provides real-time sales notifications, reminders about credit card benefits, and contextual recommendations.
• Wells Fargo. This institution has a chatbot in the form of a Fargo assistant. This application offers access to sending funds, checking account information, FICO scores, and spending summaries.

Benefits Of Сonversational AI For Banking Institutions

Organizations that have successfully implemented the use of AI in their daily work reap the benefits of their versatile capabilities. There are several ways conversational solutions improve organizations in the banking sector.

1. Advanced data analysis

Modern AI products gather data through client conversations, providing valuable insights for financial institutions. AI models used in building these solutions predict customer behavior patterns. For example, if they will close the account soon or take out a loan. This information is used for targeted marketing campaigns and churn prevention.

2. Better accessibility

With conversational AI tools, banking institutions expand their reach and client base. These products support multi-language communications, as well as text and voice input. Such conversational AI use cases open financial opportunities for clients with different physical capabilities.

3. Enhanced customer experience

Financial institutions reduce the costs of maintaining a client support staff. AI tools are available around the clock and handle multiple conversations simultaneously. This approach leads to faster response rates and issue resolution. Like customer support agents, modern chatbots offer a personalized experience for all individuals. For example, Bank Of America’s Erica chatbot helps almost 32 million clients with daily financial needs.

4. Faster document processing

Advanced AI solutions allow banks to process client documentation better. Users provide all files through the chatbot interface and receive aid with opening accounts and applying for loans. This approach minimizes the red tape associated with financial services and streamlines document processing.

5. Better up-selling and cross-selling opportunities

Conversational AI products open new income opportunities for financial organizations. With their help, it's possible to offer things like investments and loans based on the transaction history and behavior of bank clients. Chatbots that provide conversational AI for financial and banking institutions also offer personal recommendations. These factors make such solutions great tools for practical marketing conversions.

6. Lower operational costs

Banks save funds on daily operations by allowing conversational tools to help clients with transactions and answering frequently asked questions. The ability of chatbots and assistants to handle various numbers of clients makes it possible for institutions to save funds on staff. They also reduce losses related to data entry and calculation mistakes.

7. Security and fraud prevention

The addition of conversational AI in the banking sector adds a layer of security. These products spot potential fraud or unauthorized transactions by analyzing vast amounts of information faster than human agents. Banks also use AI voice recognition or chat-based verification tools to keep client accounts safe and save resources on refunds and legal fees.

Conversational AI In Banking: Implementation Challenges 

Despite the advantages of these solutions, financial institutions are reluctant to implement them. Part of it can be attributed to long-established organizations being generally resistant to progress and change. But, another part lies in the fact that banks face problems that are connected to the technological aspects of running these institutions.

1. Accuracy

Conversational AI solutions are only as accurate and reliable as the data they’re trained with. If this information is unstructured or insufficient, the large language models used in AI products will be unable to address complex issues or understand client needs. Banks will have to work on processing their data on customer interactions and feedback if they wish to work with accurate conversational tools.

2. Bias risks

While information is a critical component in the work of these products, it also causes harm in certain situations. Since AI systems make recommendations and advice based on historical data, they can favor representatives of particular demographics while discriminating against others. Using conversational AI solutions will require banks to monitor, assess, and mitigate discriminatory risks constantly.

3. Compatibility

Legacy systems used by many banks remain one of the biggest obstacles to widespread AI integration in this sector. Their central systems holding transactions and customer account data use old local software, which is challenging to pair with modern conversational AI systems. Banks must heavily invest in API development and cloud infrastructure to allow seamless communications between them.

4. Data security and privacy

Additionally, banks require rigid access control, activity logging, cybersecurity, and data encryption practices. Otherwise, they won’t be able to keep user information safe. Organizations in this sector should also work on updating their storage capabilities and implementing such techniques as tokenization, data masking, and strict access policies. These practices will help safeguard dialog logs from assistant and chatbot interactions.

How Clients Benefit From Conversational AI In Bankin

While challenges associated with AI remain, institutions that manage to overcome them offer new opportunities to their clients. Conversational products help them manage accounts and credit cards while acting as personal assistants. Here are eight use cases bank customers can expect from AI tools:

1. Making payments

Conversational AI assistants guide clients through the purchase process and help them select the correct payment methods. This process is much faster than paying with an app or a website, as chatbots perform various tasks and actions at lightning speed.

2. Reporting lost or stolen cards

Modern representatives of conversational AI in banking let customers take immediate action whenever they lose credit cards by freezing or locking them. In the past, customers were required to call the card provider and wait for a support expert to process their request. AI chatbots reduce this process down to minutes.

3. Accessing information on recent charges

Virtual helpers provide an easy way for users to track recent charges and transactions. This way, clients have better control over their subscriptions and cancel those no longer required. The latest C+R Research data shows that 42% of Americans pay for subscriptions they’ve forgotten about.

4. Getting information on account and card balances

Banking chatbots used by financial institutions allow customers to access all their account details. Modern AI solutions have user verification features, ensuring the safety of data. 36% of all American bank clients use chatbots to check their balances daily.

5. Checking exchange rates and stock prices

Conversational AI for financial needs lets clients know about different stocks, currencies, and exchange rates. These solutions access market information in real-time and provide users with accurate answers. This saves time and effort in finding this information manually on the web.

6. Providing information about the due dates of payments 

Bank clients use assistants and chatbots to ask about credit cards, bills, and loan due dates. AI helpers also remind people about upcoming payment days, reducing the risk of missed deadlines. This feature also shows clients avoidable expenses, such as unnecessary subscriptions to Audible and Duolingo.

7. Browsing offers on loans and mortgages

Chatbots built with the power of AI technology handle various requests about banking services and their latest offers. They provide information about interest rates on mortgages and loans. Instant access to the institution's databases provides the latest information and lets customers make informed decisions.

8. Transferring funds between accounts

AI chatbots help clients transfer money from one account to another. These solutions also reduce fraudulent activities by asking user-specific questions, tracking client locations, and checking their transaction history. Should the chatbots see any new patterns, they ask questions to verify that they’re talking to the rightful account owner. If the factors keep pointing to the fact that they’re talking to an impostor, the solution notifies the bank security staff.

The Future Of Conversational AI in Banking

The comprehensive implementation of artificial intelligence solutions has the power to change the banking sector. A well-planned integration with the central back-end systems will ensure that chatbots and virtual assistants access all necessary data and infrastructure. A thoughtful approach with the best ethical AI practices, accuracy, and transparency will fully automate the customer experience.

Early adopters of conversational AI products will have a competitive edge. Modern AI-based tools offer a comprehensive and personal customer experience people will find helpful and convenient. Despite the abundant evidence of the benefits, most banks aren’t too keen on investing in this technology. But, this situation can change in the next decade as more institutions follow the success of major American banks.

Conclusion

These developments clearly show the potential of conversational AI use cases in the banking sector. Their clients will better control financial activity from the convenience of mobile and web applications. This, in turn, will allow the institutions to cut operational costs and build trust with their customers, gradually building up the brand image and expanding their business.