50 years ago, a new technology swept across banking, transforming the way that consumers interacted with their financial institutions and their money. The launch of the first ATM (or cash machine), in London by Barclays, heralded a new, consumer driven focus for retail banks, with customers deciding when (and later, where) they wanted to access their money. This change allowed banks to shift their focus from applying rules (you may only withdraw money at a specific time) to meeting evolving customer needs.
Additional technological advances brought further innovation and customer benefits. Plastic started to replace the cash in consumers’ wallets, and online banking portals emerged on computers and smartphones, freeing consumers from the tyranny of opening hours, paperwork and phone calls from merchants to verify bank balances. In an increasingly competitive banking environment, consumers found themselves spoilt for choice as their banks increasingly tried to tailor their services to their customers’ changing lifestyles.
No industry can stand still, however, particularly as a new generation of consumers accustomed to smart and connected technologies has become an important market segment. This customer base has helped to drive a new technology revolution, as the retail companies they use have turned to Artificial Intelligence (AI) as a way to provide them with “always-on” service. The financial services industry must be aware: ignoring this next step forward in technology could see their organisations fall out of step with their innovative competitors working in the payments and tech space.
Long a science-fiction mainstay, it is recent developments in machine learning and data mining that enabled AI to finally crystallise into a functioning consumer technology. AI applications can now use data taken from millions of customer interactions to map out future customer needs and identify how to respond to them. By shadowing human operators working and logging their responses, these automated systems can learn an institution’s brand and tone of voice and then apply it to their customer responses. Feedback loops constantly improve the appropriateness and effectiveness of the response, with the goal of providing consumers with a seamless customer experience.
In terms of customer service, one effective way of operating these AI systems is as chatbots, which can unobtrusively float on top of an open website, without requiring pop-ups or new browser windows to be opened. This discrete approach is critical, as it ensures that the customer retains the ability to decide where and when they want to interact (or not) with the company in question. In addition, chatbots closely mirror the instant messaging services used by younger customers to communicate, making the interactions feel more personal and relevant.
While providing customers with an engaging and informative service, retailers have also found chatbots can provide a range of benefits beyond the simple fact that they extend customer service hours of a brand across 24 hours. Chatbots can be overseen by customer service operators, and in contrast to AI applications using voice control, multiple chatbots can be monitored at the same time by a single person. While the majority of conversations can and will be handled automatically by an AI application (for example, we found that an insurance client could use AI to handle 67% of online customer queries), complicated questions that require more input can be handed over to a human operator.
This ability to blend AI and human interaction should resonate strongly with financial services organisations due to their highly regulated nature. If a customer requires help with filling out an application for credit, an AI chatbot can provide discrete support. If, at any point, the customer then asks for advice or crosses a pre-configured red line, a human operator can step in to ensure compliance with financial regulations.
As an additional benefit for retail organisation, AI applications can also provide a new customer interaction model – that of uplift. An AI system can be trained to only engage with customers that will appreciate the contact (determined by detailed data analysis of millions of online customer interactions), thereby uplifting their customer experience, while monitoring but not disturbing customers that wish to be left alone. This approach could help banks to increase conversions amongst those that are amenable to being interacted with, while not impacting on customers who prefer to do their own research or not be disturbed.
The general population does not always realise that AI and chatbots are no longer a dream of a distant future, but a technology that is already live and interacting with many retail customers. Financial institutions such as retail banks need to grasp the opportunities represented by this technology, as customers will soon find it difficult to imagine a world where an online interaction or query is not immediately resolved by the company in question.