Case Studies

Financial Institution Implements Unsupervised Machine Learning to Stop Application Fraud

Financial Institution Implements Unsupervised Machine Learning to Stop Application Fraud

How DataVisor Helped:

  • The identified linkage between malicious accounts to catch all members of the fraud ring.
  • Caught fraudulent accounts at account opening time to reduce the window of exposure for the bank.
  • Detected new types of attacks without labels or training data.

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DataVisor recently partnered with one of the largest banks in the U.S. to help them reduce fraudulent applications created using synthetic or stolen identities. Read this case study to learn how DataVisor detected an additional 30% of fraudulent accounts on top of the bank’s existing in-house detection solution.

Trusted by Leading Brands

"DataVisor’s machine learning solution is the most critical component of our fraud defense as we grow in digital space, helping us minimize customer friction while defeating fraud risk."
Richard Cooney
Head of Fraud Strategy
About DataVisor

DataVisor is the leading fraud and risk management platform powered by transformational AI technology. Using proprietary machine learning algorithms, DataVisor restores trust in digital commerce by enabling organizations to proactively detect and act on fast-evolving fraud patterns, and prevent future attacks before they happen. Combining advanced analytics and an intelligence network of more than 4B global user accounts, DataVisor protects against financial losses and reputational damage across a variety of industries, including financial services, insurance, marketplaces, ecommerce, and internet platforms.