Top-notch financial services are no longer just for the elite. Although differentiated services are available for various customer profiles based on age, income, or net worth, banks have to work harder than ever now to woo and retain customers due to the commoditization of financial services. Even in financial inclusion, where profitability is not the driver, digital transformation at various levels like customer data management is useful.
Few countries have floated fintech monitoring and regulatory authorities to nurture new innovative businesses. Such initiatives, in partnership with technology companies, have made mobile and internet technologies accessible to the masses. The ubiquity of mobile-based P2P payment technologies by the likes of Venmo and Zelle in the US, Apple Pay, and the upcoming Ziina in the Middle East, PayTM, UPI, Google Pay in India have reduced cash-based payments to a minimum, especially in current times.
Advancement in Natural Language Processing (NLP) and Natural Language Understanding (NLU), have helped financial services businesses bridge the digital divide even further, by simplifying the complete customer engagement. We will focus on this aspect in the rest of this article and how we at active.ai are helping banks in the process
Let us start by looking at what are the key expectations for a customer when it comes to managing their money
- Availability – provide simple & secure interfaces to get details
- Understanding – listen and help with financial management
- Advise – be a well-meaning friend not just an agent
Availability
Customers want to be able to get any information they need on their finances at any time of the day, on their handheld device, voice assistant at home or in the car. With technologies like IoT that provide hyper-connectivity customers have started to expect to tap into their financial data in a secure manner, even at drive-throughs and point of sales.
According to a study, as long as Millenials are convinced of accessibility and security, they will sign up for banking through brands they have come to trust like Google and Amazon. Banks & insurers would be relegated to a back end service provider if they do not provide the same level of experience, which they experience in their everyday digital life.
Digital has evolved beyond mobile & internet banking over the years and has proliferated into social media apps like WhatsApp, FB messenger, digital assistants. Every business has to be available on all such platforms and provide excellent experience on each of them.
Customers can experience conversational banking over text and voice channels, using an AI-based interaction platform. This can be a differentiator in the following scenarios
- Are there any charges for upgrading my card for international usage? – rather than stopping at responding to what customer wants, the virtual assistant (VA) will provide suggestions to related questions & a simple action to enable the facility
- Use a voice assistant to check utility bill dues and pay from a linked bank account, while driving.
Conversational Banking Experience
Understanding
Consider a mother, while commuting to work, realizes that she has to send the monthly pocket money to her daughter. She can simply chat with their bank on WhatsApp or FB messenger, where the conversation can go something like this
Customer making a transaction via natural conversation
Conversational AI can also help discover what the user may be looking for even though they might not say it directly. So here is how your VA can help to uncover a hidden customer intent.
Another scenario can be when a customer asks about the features of a new Signature credit card introduced by the bank. This can be answered to the point for an NTB customer. However, for an existing credit card customer, the assistant can respond with a comparison of the customer’s existing card type and the Signature card, and even provide an enticing upgrade offer.
Machine learning (ML) from conversational data, can also help continuously engage the customers throughout the interaction, even going to the extent of anticipating and providing the next best step for that point of time considering the context, which we will discuss next.
There can be possible user utterances where the VA cannot understand what the user has typed or is not trained to handle those utterances. In such a scenario, we facilitate graceful handover to a human who can handle that specific situation and return back to the virtual assistant. Our supervised learning also helps to analyze ‘What is it that the chatbot has failed to understand?’ and extend the capabilities by continuously training it so that it handles the scenario next time. Continuous improvement is the key!
Advise
The next phase of conversational assistants (which in most cases is the differentiator) is when the assistant does not just stop at responding to what is asked of it but goes above and beyond to provide insights into ‘what is the best course of action for the user’ at that point. Consider the following options for customer delight, when the AI-based assistant
- Suggests transferring funds through another network where the fees are lower,
- Advises paying the ‘total amount due’ on their card (in a non-intrusive way), when the user asks to pay ‘minimum amount due’ on their credit card, by explaining the merits.
To summarize, we believe banks must take a holistic approach to a customer experience platform and not a siloed approach, which is typical in large institutions. According to analyst reports, AI investments in banks are the highest in the area of customer experience. We are glad to partner with institutions across the world, large and small, and help them excel in their customer service efforts.