The fraud-fighting dream team of the future likely includes machines and humans. Picture this: your credit union’s fraud prevention system flags a series of transactions as high risk. The transactions, however, are for gas and groceries. Seems fairly normal, right? The system may have gotten it wrong. Upon closer inspection from a team of data scientists and analysts, though, you discover the fraud was all too real.

What gives machines + humans true dream-team potential is the unique skillsets they each bring to the table. Machines can be fully automated to perform complex tasks and predict behavior – eliminating the need for costly, time-consuming manual reviews. This is what is known as machine learning. Humans can then further analyze the machine outputs in light of their experiences with the wider fraud environment.

In true futuristic fashion, machine learning involves teaching computers to think for themselves. The computers identify patterns, solve problems and respond as programmed for certain scenarios. “The precise nature of machine learning helps ensure fraud detection is highly accurate,” said Ashley McAlpine, fraud prevention manager at CO-OP Financial Services. “Combined with a human review, flagged transactions can be quickly verified as fraudulent or not.”

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