Machine learning is a 100% fraud-fighting priority. Is it for you?

As fraud-fighting becomes increasingly complicated, machine learning has emerged as a new holy grail technology for fraud detection. In “Machine Learning: Fraud Is Now a Competitive Issue,” 65 percent of the senior fraud and data analytics executives at North American financial institutions Aite Group interviewed say the priority for investment in machine-learning analytics for fraud mitigation is very high and a key area of investment; another 35 percent call it a moderate priority. Yet, only 40 percent of interviewees have an ML-enabling platform deployed or in production, with another 10 percent with proofs of concept underway.

The question for credit unions is, how and when will machine learning make a difference in your fraud-fighting efforts?

Insight Vault caught up with Nick Calcanes, CO-OP’s chief information officer, and Paulo Marques, chief technology officer and co-founder of pioneering AI developer Feedzai to get some answers. Full disclosure: CO-OP is teaming up with Feedzai on a new machine-learning security tool for the credit union industry that is expected to deploy in 2018.

Here are five pointed questions about machine learning, fraud and how your credit union might fit in:

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