For years, fraudsters would simply take numbers from credit or debit cards and print them onto blank plastic cards to use at brick-and-mortar stores. But in 2015, Visa and Mastercard mandated that banks and merchants introduce EMV — chip card technology, which made it possible for merchants to start requesting a PIN for each transaction.Nevertheless, experts predict online credit card fraud to soar to a whopping $32 billion in 2020.Putting it into perspective, this amount is superior to the profits posted recently by some worldwide household, blue chip companies in 2017, such as Coca-Cola ($2 billions), Warren Buffet's Berkshire Hathaway ($24 billions) and JP Morgan Chase ($23.5 billions).In addition to the implementation of chip card technology, companies have been investing massive amounts in other technologies for detecting fraudulent transactions.Would Machine Learning & AI constitute great allies in this battle?Classification ProblemsIn Machine Learning, problems like fraud detection are usually framed as classification problems —predicting a discrete class label output given a data observation.


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