Hello readers, as promised, we are here with our 2nd blog in the series of blogs on “AI in Banking and Financial Services”, focusing on Chatbots.
As discussed in the previous blog AI is helping banks automate AML investigations. By implementing AI, the banking system is able to segment customers according to thresholds, analyze transactions, and customer profiling and scoring. In addition to pattern recognition, AI technology is also extensively being used to enhance customer service experience, primarily through chatbots.
There is nothing like interacting with an experienced banker who knows all the procedures, has all the knowledge, and is also aware of our preferences as far as financial products are concerned. An advice from such a banker is lapped up by the customer and helps increases the loyalty and business from the customer to the bank.
Now, a multi-million dollar question is how can you make available such bankers to all the customers? And if banks automate the query resolution by way of FAQ’s or through a program that answers all the queries, how does a bank take next leap and make that program so intelligent that it almost sounds like a human?
This is where chatbots and other machine learning software fill in the void. These machine and software know of banking processes, rules and at the same time are emotionally intelligent to strike conversation like humans and cross sell other products the way humans do. So, these align recommendation engines with the chat bots.
Let’s understand the above concept with the help of a few examples:
Example 1 –
Normally, financial advice is offered by professional financial planners, but since it involves a certain cost, it is only availed by high net worth individuals. With advent of AI based chatbots, this service is being democratized, as now the service becomes scalable for banks.
Answers to queries such as how much the customer needs to save to reach a certain financial goal? Or where they are spending maximum money? Can be answered by chatbots.
As we see in the given example the chatbot is seen giving information about current balance in account and telling the customer that it will take five months to reach their goal given the rate of deposit and expenses.
Example 2 –
Similar to above example here we can see that chatbot is providing financial information (bank balance) to the customer. This data is fetched from backend system automatically and provided in human language to customer. Other examples of queries can be who is nominee in my account? When is the last date of filing tax returns? And others.
Example 3 –
Chatbot can also provide instant information on the types of loans the bank offers. The system also records the IMEI number to check if customer with same mobile user had earlier applied for any loan. This can help keep a check on fraudulent applicants.
Example 4 –
Chatbot can also guide a customer to the nearest ATM or branch.
Chatbots is an excellent tool promising prompt and impressive customer service. Implementing the technology not only helps banks reduce the turnaround time at customer girivence but also lower their operating expense.
Thank you once again for reading our blog. Let us know your views and suggestions in the comments below. Our next blog will focus on another crucial topic on AI in Banking – Fraud Detection.
Until Next Time!
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