When you hear of AI and machine learning, it’s easy to think of technology companies leading the charge. Capital One is determined to change that.
“My first thought when Capital One approached me was ‘well it makes sense they use machine learning to predict lending decisions and other financial forecasting and that’ll be about it.’ So I wasn’t terribly enthusiastic,” said Nitzan Mekel, managing vice president of machine learning at Capital One.
“But what really turned me on to the opportunity, and what gets me excited everyday now, is the fact that we use AI and machine learning pretty much in every facet of our business.”
In a conversation with AI Podcast host Noah Kravitz, Mekel explained how the banking giant is integrating AI and machine learning into its customer-facing applications such as fraud-monitoring and detection, call center operations and customer experience.
“From a customer standpoint, we’re leveraging machine learning to help customers become more financially empowered,” Mekel said. “We want them to make predictions about upcoming bills, detect irregular expenses … and of course enhance their digital experience and their satisfaction with us as a consumer.”
One of the AI applications available now is Eno, an intelligent assistant that Capital One clients can use to track and manage their accounts.
According to Mekel, the increasing demand to deliver real-time experiences is a main contributor to the growth in AI as “people are now pretty much accustomed to everything being in real time.”
Realizing this, Capital One has been focusing its AI efforts on real-time fraud prevention with tools such as interactive alerts, easy-to-report fraud transactions, and the ability to lock cards in real time.
With machine learning in the picture, Mekel is positive that customers will receive better service from the finance industry than before.
“The whole relationship between a customer and a bank changes because now we can be a real advocate for them in the most direct possible way, while before there was just this big gap and a customer was, for lack of a better word, sort of a number,” Mekel said. “Now we can understand their context.”