In Part One of this blog series, we highlighted four recurring themes and overarching trends on display from the most prominent thought leaders in artificial intelligence and financial services during the Bank AI 2017 conference in Boston, MA. The goal of this post is to translate theory into practice, reviewing specific use cases from three major banks—Bank of America, Wells Fargo and RBC—that are active in the artificial intelligence space. From this, we can gain a glimpse into how AI is viewed at some of the most largest banks and start to understand the role it will play at their firm and the larger industry as a whole.
1) Keynote speaker Michelle Moore, Head of Digital Banking at Bank of America, showed off the firm’s recently launched AI assistant, “Erica,” which is available in the firm’s mobile app. Erica was designed to make using the mobile app easier and quicker. The assistant provides a list of the most common topics based on the user’s interactions and dynamically suggests helpful ideas based on actions. Erica can answer account-specific and general questions, complete transactions and provide budgeting and goals help. Eventually, it will evolve to provide better personal finance recommendations as well. Bank of America envisions Erica migrating to other platforms including the website, call centers and Merrill Lynch and Edge apps, ultimately replacing the Help sections on these platforms and providing a seamless omnichannel experience.
2) Brian Pearce, Senior Vice President of Enterprise Artificial Intelligence at Wells Fargo, also discussed ways AI can be useful to customers. Pearce noted that Wells Fargo made a concerted effort to take AI out of testing in Labs and begin to solve business problems. Aside from chatbots, Wells Fargo plans to use AI in four main areas:
- Banker Assistants – AI will be used to support bankers to quickly provide transaction information and other pertinent client details. Pearce used the example of a bereavement interaction where the WF team would be able to focus on customer engagement while the AI tool is busy capturing the information necessary to manage the case. AI would deftly collect the required data and pull the relevant documentation from a variety of internal libraries.
- Custom Experiences – Wells Fargo will use AI to make predictions and use that analysis to drive experiences. The program could analyze customer transactions, payments and other data to generate, prioritize and deliver intelligent insights. This would allow the firm to offer unique experiences at scale.
- Operations Excellence – Pearce noted that AI doesn’t have to be customer-facing. Wells Fargo plans to overhaul its back-office with robotic process operation changes. The firm feels this is a huge opportunity that carries a relatively low risk. Pearce believes this is the area where we will see the first true AI applications.
- Understand – Review content to glean insights and uncover opportunities. Wells Fargo is working on an AI program that can consume emails, listen to voice conversations and go through texts to help understand what its customers are saying. Natural language processing and AI can drive a lot of insights from this data.
3) David Kapauan, Distinguished Architect at RBC, discussed how implementing an AI-powered conversational interface altered their relationship with clients. Kapauan stated that RBC is focusing on voice interactions with the hope of becoming a “financial version of Siri” for its clients. One of their main goals was converting their entire IVR platform to natural language understanding, highlighting the fact that every second they can save in their call center is worth $1m to the firm. Interestingly, Kapauan noted that the voice talent has to be better and sound more natural compared to traditional IVR systems, which sound mechanical, if clients are to embrace the change.