Case Studies

Financial Institution Implements Unsupervised Machine Learning to Stop Application Fraud

Financial Institution Implements Unsupervised Machine Learning to Stop Application Fraud

Complimentary Resource

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.

How DataVisor Helped:

  1. Identified linkage between malicious accounts to catch all members of the fraud ring.
  2. Caught fraudulent accounts at account opening time to reduce the window of exposure for the bank.
  3. Detected new types of attacks without labels or training data.
About DataVisor

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