Berry Levine says, “When it comes to user fraud, marketers should push for machine learning systems to replace rule-based ones.

That’s the viewpoint of Jason Tan, CEO/co-founder of San Francisco-based Sift Science. Of course, it would be shocking if he didn’t feel that way, since his company — started by several former Google engineers — is one of several startups that are now offering machine learning-based user fraud detection.

He recently made the case to me that machine learning should be on every marketer’s wish list.

Because, he said, rules-based systems throw up hoops to users who are trying to buy something or trying to register. These hoops include captchas, those squiggly images of letters and numbers that humans should be able to decipher and which software agents — bots — cannot.

Hoops can also mean security questions or reviews by human analysts. Fraudsters can include humans wielding stolen credit card numbers“.

Why Marketers Should Push for Machine Learning-Based Fraud Detection

Marketing Land

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