Fraud protection is a race against scale. For instance, Mastercard’s network processes roughly 160 billion transactions a year, and experiences surges of 70,000 transactions a second during peak periods (like the December holiday rush). Finding the fraudulent purchases among those — without chasing false alarms — is an incredible task, which is why fraudsters have been able to game the system. But now, sophisticated AI models can probe down to individual transactions, pinpointing the ones that seem suspicious — in milliseconds’ time. This is the heart of Mastercard’s flagship fraud platform, Decision Intelligence Pro (DI Pro). “DI Pro is specifically looking at each transaction and the risk associated with it,” Johan Gerber, Mastercard’s EVP of security solutions, said in a recent VB Beyond the Pilot podcast. “The fundamental problem we’re trying to solve here is assessing in real time.”How DI Pro worksMastercard’s DI Pro was built for latency and speed. From the moment a consumer taps a card or clicks “buy,” that transaction flows through Mastercard’s orchestration layer, back onto the network, and then on to the issuing bank. Typically, this occurs in less than 300 milliseconds. Ultimately, the bank makes the approve-or-decline decision, but the quality of that decision depends on Mastercard’s ability to deliver a precise, contextualized risk score based on whether the transaction could be fraudulent. Complicating this whole process is the fact that they’re not looking for anomalies, per se; they’re looking for transactions that, by design, are similar to consumer behavior. At the core of DI Pro is a recurrent neural network (RNN) that Mastercard refers to as an “inverse recommender” architecture. This treats fraud detection as a rec …
