How will the banking industry use AI to improve CX?
The preponderant use of AI (artificial intelligence) technology in recent years has completely changed the way customers and banks communicate with each other.
While banks initially used AI primarily for chatbot technology, significant progress within the field means that the use of AI now goes far beyond this. Continued use of innovative AI technologies in new and exciting ways within the world of banking will have a significant impact on the industry, to the point where they will totally transform the customer experience. Here’s how:
The use of AI will enable banks to help customers keep their accounts more secure by detecting any anomalies and fraudulent activities much quicker than previously possible.
The beauty of using AI and machine learning (ML) in this way lies in their ability to understand what is ‘normal’ for each account or card by recognizing patterns based on past transactions and behaviors.
With AI capable of detecting any deviations from the normal patterns faster than currently possible, banks will be able to inform their customers if their accounts appear to have had unusual activity much quicker. The customer can then investigate the transaction and determine if it is fraud or just out of the ordinary.
In the future, we may get to a point where fraud detection can be done in real-time in order to stop fraudulent transactions happening altogether. In these cases, we could see the account being frozen or the card being blocked in order to prevent the transaction from being completed. However, this is still some way off becoming a reality.
AI is also elevating the way in which banks can communicate with their customers. In effect, this new technology is enabling banks to become much smarter when it comes to customer service and one of the most impressive ways it does this is through employing tone and language analysis techniques to determine the customer’s mood or state of mind, during a phone call for example.
This is also referred to as customer sentiment analysis and can be of inestimable value to banks, as it offers customer service representatives appropriate suggestions to resolving complaints, for instance – all tailored to that particular customer’s situation and temperament at the time.
What’s more is that all this can happen in real-time, meaning banks will be able to improve the speed and quality of their customer service. To put it in perspective, research has found that almost three-quarters (72 percent) of companies believe that sentiment analysis leads to improved customer experience.
According to Gartner, by 2020 consumers will manage 85 percent of their total business interactions with banks through fintech chatbots.
Banks can also begin to use continuous machine learning to gain a better understanding of the data they collect in order to make predictions about customers, understand their future behavior and ensure that the level of service they desire is maintained.
For example, by recognizing patterns in people’s spending behavior, banks can redistribute credit limits. So, if a person is consistently spending a certain amount, the bank will know that’s how much they should lend them.
This gives banks a mathematical way of understanding the optimal way to provide credit. Consequently, the customer benefits from having the right amount of credit made available to them, while banks gain a better understanding of their customers thus reducing the risk of lending too much, for instance.
Looking further ahead
AI will not only allow banks to offer a better customer experience but it is thought they could also see savings of between 20-25 percent across IT operations.
Additionally, according to Accenture, AI will allow bank employees to spend more time on exceptional work: 20 percent of non-routine tasks that drive 80 percent of value creation. This means that individuals will be able to move into more value-adding roles and be supported by AI, rather than being replaced by it. AI will, therefore, offer substantial benefits to bank employees as well as helping to enhance the customer experience.
This article was contributed by David Duan, Data Science Stream Lead & Principal Data Scientist at Fraedom.
30 March 2023
30 March 2023
30 March 2023