To Mekel-BobrovвЂ™s point, false positives are well known for irritating and even alienating customers. ItвЂ™s helping us be protective, but not overprotective.вЂќ But on the other, itвЂ™s preventing customers from having a negative experience where theyвЂ™re being declined when they shouldnвЂ™t be. вЂњOn the one hand, this is an essential component of our defensive strategy. But at the same time, itвЂ™s a situation where there are two sides of the same coin,вЂќ Mekel-Bobrov says. вЂњWith machine learning, weвЂ™re protecting our customers by preventing fraud. This even applies to the bankвЂ™s call centers, where speech recognition technology is being used in an automated training and validation system that has roughly doubled accuracy in the past 18 months. With massively more data, longer data history and advanced algorithms, Capital One is focused on leveraging machine learning to revolutionize how it manages fraud.ДЇor Capital One, using data analytics and machine learning on AWS brings a host of new opportunities to customize their usersвЂ™ experience and gain more insight on engaging with customers, as well as helping inform key business decisions. When suspicious activity occurs, Capital One will automatically alert customers, walk them through fraud reporting steps, help them lock their card and order a new one, and unlock a temporary card so there is no interruption in their ability to spend their money. Leveraging a broad suite of machine learning tools and frameworks, such as TensorFlow on Amazon Web Services (AWS), Capital One has the ability to analyze large sums of data, which helps it detect and prevent fraud in real time. This allows us to make more precise predictions around whether an activity is fraudulent or not.вЂќ

вЂњWeвЂ™re continuously building more sophisticated systems that can leverage a variety of data, structured and unstructured. вЂњWeвЂ™ve recognized over the past number of years the importance of leveraging machine learning to enhance the user experience, as well as to help us make more informed decisions around engaging with our customers,вЂќ says Nitzan Mekel-Bobrov, Ph.D., managing vice president of machine learning at Capital One. With large masses of data distributed across numerous storage centers, machine learning has been invaluable as Capital One works to better protect its customersвЂ™ financial well-being-helping them become more financially empowered, look out for fraud and work to reduce false positives, and better manage their spending.

According to a 2018 report from the White House council of economic advisors, malicious cyber activity cost the economy between $57 billion and $109 billion in recent years, with the financial sector seeing the most breaches of any industry. Some of the worldвЂ™s worst cyber criminals focus on the financial services industry, making security all the more vital. One area where Capital One is applying machine learning is in the realm of fraud detection.

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