Experian teams with DataVisor to spot early-stage fraud attacks

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Experian is adding DataVisor, which specializes in advanced machine learning, to its CrossCore platform to identify unusual patterns signaling new fraud activity.

By integrating DataVisor’s dCube solution into the CrossCore hub, Experian will enhance its ability to detect fraudulent signals at the earliest stage, Experian said in a Wednesday press release.

Users may leverage dCube's ML capabilities without the need to add any new training data or labels, while preserving the ability to build and experiment with existing models and data inputs, the release said.

CrossCore is Experian's tech hub established in 2016 to house various fraud tools it's acquired, such as Danal, and third-party technology, such as BioCatch.

“We are committed to providing businesses with resources to more easily detect fraud behavior and protect people’s identities and advanced technology such as machine learning is pivotal to that process,” said Steve Pulley, Experian’s executive vice president of global identity and fraud solutions, in the release.

“We’re aligned in the belief that machine learning is one of the keys to delivering frictionless customer experiences through advanced fraud prevention strategies,” said Yinglian Xie, DataVisor’s co-founder and CEO.

DataVisor was founded in San Francisco in 2013 by Xie and Fang Yu, CTO, to develop unsupervised machine learning technology that spots fraudulent attacks before they’re fully deployed. DataVisor has raised about $55 million in venture financing to date.

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Fraud detection Payment fraud Fraud prevention Artificial intelligence Experian
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