As the banking industry continues to evolve, financial institutions are turning to technology to provide better service and cost savings. One area where technology is making a significant impact is through the use of conversational AI, commonly known as chatbots. These chatbots use natural language processing and machine learning to understand and respond to customer inquiries in a human-like manner. In this blog post, we will explore the top 10 use cases for conversational AI in banking and how this technology can help improve customer service, reduce costs, and create new revenue streams.

Let’s take a look at the top 10 use cases for conversational AI in banking.

10 Conversational AI use cases banks cannot ignore in 2023

1. Automate FAQs –

Chatbots can be used to provide quick and efficient responses to common customer inquiries, such as account balances and transaction history. This can free up human customer service representatives to handle more complex issues, while also providing customers with 24/7 access to information. Furthermore, chatbots can be designed to understand natural language, which means that customers can ask their questions in a way that feels more natural to them, rather than needing to use specific keywords or phrases.

2. Fraud detection and prevention –

Chatbots can be trained to detect and flag suspicious activity on customer accounts, and can even be integrated with other systems, such as machine learning models, to improve their accuracy. Furthermore, conversational AI can also be used to conduct identity verification when a customer initiates a sensitive transaction, such as making a wire transfer, or changing their address or phone number. This can improve security while providing a seamless customer experience.

3. Improve loan application process –

The chatbot can interact with the customer, understand their needs and guide the customer through the process, by collecting information needed and verifying the identity of the borrower. It can also assist with document submission and help the customer to understand the terms and conditions of the loan and the available options.

4. Financial education and planning –

Chatbots can be designed to provide customers with information about various financial products and services, such as savings accounts and retirement plans, and can also be used to help customers create personalized financial plans. This can help to educate customers and empower them to make better financial decisions, which can ultimately lead to better outcomes for both the customer and the bank.

5. Improve internal processes –

Chatbots can be used to automate tasks such as data entry, account creation, and information retrieval, which can help to reduce costs and improve efficiency. Additionally, conversational AI can also be used to assist bank employees with tasks such as training and onboarding, which can help to improve employee productivity and satisfaction.

6. Wealth management –

Chatbots can be used to provide personalized financial advice to customers, based on their investment goals, risk tolerance and current portfolio. This can help customers make more informed investment decisions and achieve their financial goals. Additionally, chatbots can also be used to monitor the performance of investments and provide real-time updates to customers.

7. Personal finance management –

Chatbots can be integrated with customers’ banking and financial accounts to provide a holistic view of their financial situation, including balances, transaction history, bills, and budgeting. This can help customers gain a better understanding of their spending patterns and make more informed financial decisions. Additionally, conversational AI can also be used to provide personalized financial coaching, such as suggestions for reducing expenses or increasing savings.

8. Faster collection and recoveries –

Chatbots can be trained to interact with customers who have past-due loans or credit card balances. They can be programmed to negotiate with customers to set up a payment plan or offer a settlement, which can be more efficient and less costly than traditional collections methods. Additionally, conversational AI can also be used to assist customers in understanding their options for consolidating debt or obtaining a loan to pay off outstanding balances.

9. Personalized experience –

conversational AI can also be used to provide personalized offers, promotions and discounts to customers based on their spending patterns, location, and other data. This can help banks increase customer loyalty, improve sales and create more profitable customer relationships.

10. Customer acquisition –

Chatbots can be used to engage with potential customers and guide them through the process of opening an account or applying for a loan. The chatbot can provide information about the bank’s products and services, answer questions, and assist with the completion of the application process. Additionally, the chatbot can also be integrated with other marketing platforms such as social media, which can help the bank reach a wider audience and increase the number of leads generated.
For example, a chatbot could be placed on a bank’s website, where it can interact with visitors and provide information about various products and services. The chatbot can then collect information about the visitor, such as their contact details and preferred products, and pass this information on to a sales team for follow-up. This can help banks to increase the conversion rate of website visitors into customers and improve their customer acquisition process.

Is the future of banking looking conversational?

Conversational AI has the potential to revolutionize the banking industry by improving customer service, streamlining various processes, increasing security and providing new opportunities for growth and revenue. With its ability to understand natural language and provide quick and efficient responses to common customer inquiries, detect and prevent fraud, simplify loan application process, assist with financial education and personal financial management, improve collections and recovery process, assist underbanked population, provide personalized offers and customer acquisition, the technology can help financial institutions provide better service to their customers, while also improving efficiency and reducing costs.

The use cases for conversational AI in banking are numerous and varied, and it’s clear that this technology can bring significant benefits to both financial institutions and their customers. We can expect to see more and more financial institutions adopt this technology in the coming years. The possibilities are endless, and it’s an exciting time for the banking industry to stay competitive in the marketplace.