Case Studies

Application Fraud: Leading U.S. Credit Card Issuer Saves $15M

Leading U.S. Credit Card Issuer Uses DataVisor’s Machine Learning Solution to Reduce Application Fraud Losses

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Credit card fraud can result in huge financial losses for both credit card issuers and their customers — but too many false positives lead to missed revenue opportunities. How do you strike a balance?

Large financial losses from coordinated third-party and synthetic fraud. Delayed application approvals and costly manual reviews due to too many false positives. Skyrocketing operational costs and increasing friction for customers. Something had to be done.

One major U.S. credit card issuer cracked the code with DataVisor’s advanced fraud detection solutions.

Read the full case study to learn how this major credit card issuer:

Proactively captured coordinated and unknown fraud with 94% detection accuracy
Created frictionless experiences for good customers
Captured 25% more fraud while reducing false positives
Saved $15 million in fraud losses and operations in one year

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

Bots attacks cost companies roughly $80 billion a year. How do they work, and how can you stop them? In our latest ebook, DataVisor CTO and co-founder, Fang Yu, explains why coordinated bot attacks are so difficult to detect and prevent, and shares proactive strategies for protecting your organization.