Case Study

Financial Institution Implements Unsupervised Machine Learning to Stop Application Fraud

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. Identify linkage between malicious accounts to catch all members of the fraud ring.
  2. Catch fraudulent accounts at account opening time to reduce the window of exposure for the bank.
  3. Detect new types of attacks without labels or training data.

Download the Case Study:

2018-08-24T16:30:48+00:00 April 28th, 2018|Case Studies|