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

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Capital One has a 99% success rate when it comes to understanding customer responses to an SMS fraud alert, Ken Dodelin, vice president of mobile, web, conversational AI and messaging products at Capital One, said in a discussion about how the bank harnesses the power of personalization and automation at VentureBeat’s Transform 2021 virtual conference today.

When Capital One notices an anomaly in a customer’s transactions, it reaches out to the customer over SMS and asks the customer to verify the transaction details. If the customer doesn’t recognize the transaction, then it is clear it was fraudulent and Capital One marks it accordingly.

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

The company started to consider using AI for customer service in 2016, when it was one of the early recipients of Amazon Echo devices. Back then, Amazon was looking for partners in various industries to look at how they might create a conversational experience. Capital One became the first bank to develop a skill — a special program that enabled customers to do things on Amazon platforms. In the following years, the company started to incorporate natural language understanding in to its SMS alerts, as well as website and mobile apps.

The current version of the AI assistant has evolved a lot from the initial vision, Dodelin said. First, the number of places where the assistant is available to chat with customers has increased. Whether the customer is inquiring about the bank or a car loan, there is a place for them to ask questions about their account. Second, the company said that it hasn’t restricted themselves 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 that customers would expect from a human assistant.

One challenge Capital One had to figure out what what to do if the customer wasn’t something other than one of 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. However, when creating an experience, it is important to remember that customers are being contacted under very different circumstances. A moment of levity may not be appropriate during a moment of emotional and financial stress, for example.

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

Another challenge is anticipating the breadth of questions customers have. Many times, Dodelin said, customers encounter frustration and don’t have the outlet to express that other than having a human assistant picking up the phone. Learning more about those experiences helps the AI assistant to provide better answers, as well as adjusting the options of the user interface to begin with.

“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 in the credit card business and has over time 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.

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