Capital One uses NLP to discuss potential fraud with customers over SMS

Capital One has a 99% success rate when it comes to understanding customer responses to an SMS fraud alert, according to Ken Dodelin, the company’s VP of mobile, web, conversational AI, and messaging products. Dodelin was speaking today about how the bank harnesses the power of personalization and automation in a conversation with VentureBeat senior reporter Sage Lazzaro at VentureBeat’s Transform 2021 virtual conference.

When Capital One notices an anomaly in a customer’s transactions, it reaches out over SMS and asks the customer to verify those transaction details. If the customer doesn’t recognize the transaction, Capital One can proceed to treat it as fraudulent.

By adding a third-party natural language processing/understanding solution, the AI assistant Eno is able to understand customers’ written responses, such as “that was me shopping in Philadelphia,” which is not easy for machines to understand, Dodelin said.

Capital One first considered using AI for customer service in 2016, when the company was among the early recipients of Amazon Echo devices. Back then, Amazon was searching for partners across industries to see how they might create a conversational experience. Capital One said it became the first bank to develop a skill — a special program that enabled customers to accomplish tasks on Amazon platforms. In the following years, Capital One started to incorporate natural language understanding into its SMS alerts, as well as its website and mobile apps.

The current AI assistant has evolved a lot from the initial version, Dodelin said. First, the assistant is available to chat with customers in more places. Whether the customer is inquiring about the bank or a car loan, they have an opportunity to ask questions about their account. Second, the company said it hasn’t restricted chats to conversations initiated by the customer. The company relies on its advanced data infrastructure to anticipate customer needs and reach out proactively, either through push notifications or email. The interaction would include important information and actions customers would expect from a human assistant.

One challenge Capital One had to address was what to do if the customer wanted something not included in the options displayed on the screen. “Now we have to not just design experiences for the things we expect them to get, but continuously learn about all the other things that are coming in and the different ways they are coming in,” Dodelin said.

Context matters when applying AI technologies to customer service. In many cases, scripts are relatively consistent, regardless of who the customer is or their specific circumstances. But when creating an experience, it is important to remember that customers are being contacted under very different circumstances. Levity may not be appropriate during a moment of emotional and financial stress, for example.

Capital One has continued to enhance the service so it will proactively anticipate where a customer might need help and respond in an appropriate tone, Dodelin said.

Another challenge is anticipating the breadth of questions customers have. Customers who encounter issues often lack an outlet to express their frustration beyond having a human assistant pick up the phone, he said. Learning more about those experiences helps the AI assistant provide better answers and lets the company adjust which options are included in the user interface.

“As we learn more, we got better and expanded the audience that [the AI assistant] is available to,” Dodelin said. Capital One did not make the service available to all customers but started with a small segment of its credit card business. Over time, the company has opened the service to more customers.

“It’s a lot of work done by some very talented people here at Capital One to try to make it successful in all these different circumstances,” Dodelin concluded.