Many merchants are increasingly turning to machine learning (ML) and artificial intelligence (AI) to help make faster and smarter decisions to automatically approve good transactions and reject fraudulent ones. The problem is that many companies that claim to use AI are just using rudimentary ML based on simple data. However, there is a better world on the horizon, where unsupervised and supervised ML come together and use technology to look at the patterns of safety that exist and weigh them against risk signals and anomalies to catch things that are “low safety” and high risk, including new types of fraud attacks. This is the sweet spot of stopping fraud and maximizing revenue.

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