The use of artificial intelligence (AI) in banking is nothing new. If you’ve ever spoken to a chatbot online, you can be sure that AI has been at play. The preponderant use of AI technology in recent years has completely changed the way that customers and banks communicate with each other; and thanks to significant progress within the field, AI today is about much more than chatbots.
The further use of innovative AI technologies in the banking world will have a significant impact on the industry to the point where they can totally transform the customer experience. Here’s how:
AI is definitely elevating the ways in which banks 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. 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 for resolving complaints, for instance—all tailored to that particular customer’s situation and temperament at the time.
What’s more, all of this can happen in real-time. Gone are the days of waiting on the phone endlessly before speaking to someone who can help. Thanks to this technology, 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.
Further to this, natural language processing (NLP) can be used to help chatbots understand exactly what is being said so they can form adequate responses to queries rather than generic ones based on keywords. This means that customers will be able to get the same level of service that they have come to expect from their banks but without having to visit a branch or call a helpline.
Thanks to the introduction of sentiment analysis and other AI-driven initiatives, the evolution of chatbots will continue to change the ways banks interact with their customers, enabling customers’ queries to be answered quickly and effectively. This will reduce the number of customers needing to call and speak directly to a bank employee, as AI will be able to answer the majority of questions or provide the required information.
According to Gartner, by 2020, consumers will manage 85 percent of their total business interactions with banks through fintech chatbots. Additionally, it is estimated that the operational cost savings from using chatbots in banking will reach $7.3 billion globally by 2023. With extra resources and finances freed up by the use of chatbots, banks will be able to invest in new technologies and services, streamline their operations, reduce service costs and improve their customers’ experiences while also serving more people, more quickly.
Although there is no doubt that the use of AI in chatbots will allow banks to offer a higher level of service and better, faster communications, their use won’t replace human interaction completely. Instead, the use of customer-sentiment analysis in customer services will support those working in banks. In these scenarios, AI will suggest responses for bank workers and how best to phrase their replies based on the information they’ve gathered on customers and what their language says about how they are feeling.
Additionally, through the use of AI, banks will be able to help customers keep their accounts more secure by detecting any anomalies in their accounts 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 recognising patterns based on past transactions and behaviours.
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. Certainly, anomalous transactions aren’t always fraud; it just means that they’re out of the ordinary and need more investigation, and flagging them for customers will allow for this. Being able to identify anomalies faster could be significant for businesses in particular as it will allow them to pick up on any misuse of their accounts and deal with it immediately. In cases in which fraud has occurred, businesses will be able to get to the root of the problem quickly, rather than, for example, finding out months down the line after the employee to whom the transaction relates has moved on.
In addition to helping reduce the number of false negatives (when real threats are missed), AI can also help banks reduce the number of false positives (situations in which real transactions are treated as fraud). False positives, while well-meaning, can be frustrating for customers, particularly if they prevent them from carrying out transactions or block their accounts.
In the future, we may get to the point at which 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.
Knowing the customer and personalisation
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 behaviours and ensure that the levels of service they desire are maintained. For example, by recognising patterns in people’s spending behaviours, banks can redistribute credit limits. So, if a person is consistently spending X 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. As such, the customer benefits from having the right amount of credit made available to them, while the bank benefits from having a better understanding of their customers, reducing the risks of lending.
Banks can also use AI to create more personalised customer experiences and to ensure they offer their customers the products and services most likely to be of interest to or benefit them. In this respect, AI would recognise patterns in spending and use this to determine which loans or credit cards would be best for certain customers. This means that the customer won’t be inundated with all of the bank’s offers or product information and will receive only those deemed most relevant to him or her. AI will also be able to flag how the individual tends to interact with banks—for example, whether he or she prefers to use online or telephone banking. This will then enable the bank to use this information to personalise the way it communicates with the customer, choosing the method that the individual is known to prefer. Considering 80 percent of consumers say they are more likely to do business with a company that offers personalised experiences, this could help banks to retain customers and may also enable them to attract new ones.
By using AI to offer better customer experience, banks will not only get ahead of the competition but can also expect to see savings of between 20 to 25 percent across IT (information technology) operations. However, while AI is a valuable asset for banks, it should be used to support their existing workforces by taking on some of the more menial tasks. According to Accenture, using AI will allow people to spend more time on exceptional work: the 20 percent of non-routine tasks that drive 80 percent of value creation. This means that bank employees will be able to move into more value-adding roles and be supported by AI rather than being replaced by it. The use of AI will release pressure points for employees and allow them to derive greater creativity and value from their roles.
Ultimately, the use of AI will enhance the customer experience offered by banks and improve the ways through which they serve customers, allowing them to do so faster, more effectively and with added security.