Other parts of this series:
In the previous post of this series my colleague Alan McIntyre introduced two strategic pillars, comprising a set of actions that banks can take to increase their advisory trust, help improve customers’ financial well-being and, thus, grow their revenue by an average nine percent over time. The backbone of such purpose-driven banking, we believe, is digital conversations.
The objective is to have digital conversations similar to those a customer would have with a bank’s customer service agent, who comfortably handles complex queries and solves problems. These engagements at their best are characterized by their intelligence and humanity. The good news is that customers want to have such digital conversations—our research shows that two-thirds of millennials would rather talk to a chatbot than a human, likely because they’ve grown up in a highly digital environment and trust the technology.
The technology needed for such conversations—from advanced data analytics and chatbots to change-data capture and micro-segmentation—is readily available. However, implementation has fallen short. The conversational tools in place at most banks are functional, but often more akin to glorified FAQ tools. They simply point customers to another website or provide long legalistic answers. They’re not conversations you would ever have had with a representative of your bank, nor can they handle complex queries or solve problems. In many cases, customers reach an impasse without the information they need and have no place to go.
How can banks use modern technology to move beyond such dead-end interactions? How can they put humanity into digital conversations to deliver intelligent experiences and build trusted relationships? What does that look like?
Let us assume a millennial customer, Mia, has a credit card account with Bank A. She uses IVR monthly to get transactional information about her account, set reminders or pay her bill. We know from data sourced outside of Bank A that she is searching for mortgage information and has been saving money at Bank B for a number of years.
With this insight, Bank A predicts Mia’s monthly IVR call and, in the course of it, introduces her to a virtual assistant that, in a simple way, offers her a high-yield savings account. She accepts the offer, whereupon the bot helps her open and customize the account, using e-sign for the application and answering all her questions. Bank A then offers her easy-to-understand information on savings and home buying, and the opportunity to connect with a human agent. This demonstrates the bank’s understanding of Mia’s situation and its ability to help her achieve her financial goals.
The architecture behind such a conversation uses data very differently than is the case in most banks today. Rather than being static, the data is viewed as dynamic and flowing through the bank. Real-time, tabular and instructional data is pulled into the data lake from the cloud so that advanced analytics can help the bank understand the customer’s circumstances, apply its service platform and present solutions through an application. This intelligent experience architecture is illustrated below.
Enabling such a strategy when confronted by legacy systems and technical debt requires digital decoupling. This releases data from the core and then builds around it a system of engagement and information—or a digital memory—specific to a customer. It’s how banks can replicate branch-like advisory services and put humanity back into every digital banking experience.
Getting there starts with refocusing a bank’s purpose on the customer, building trust and developing win-win propositions. Those that achieve this will be recognized as the best institutions to bank with and will grow accordingly.
For more on this topic, explore more of our Purpose-Driven Banking content: