arrow left facebook twitter linkedin medium menu play circle

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

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

Download the resource:

Popular Posts

Intelligent solutions. Informed decisions. Unrivaled results.

Q2 2020 Digital Fraud Trends Report

Learn More

Mobile channels generate a significant majority of the traffic that flows to online services and platforms, and mobile apps account for 75% of all traffic. Download this report to understand how to manage mobile fraud and mitigate its risks.

The State of Mobile Fraud: A DataVisor Special Report…

A Guide to Centralizing Data Intelligence

Learn More

Discover AI-powered fraud strategies for preventing financial and reputational damage in this powerful e-book.

Online marketplaces withstand a complicated array of fraud attacks—spam, scam, and all points in between. Only the most comprehensive, proactive AI-powered solutions can fully protect against reputational and financial damage. This e-book details the entire lifecycle of a fraud attack, and lays out…

A Practical Guide to Eliminating False Positives in Fraud Management

Learn More

This e-book explores the next generation of fraud prevention technology, which applies unsupervised machine learning to reduce false positives and risk.

This e-book explores the next generation of fraud prevention technology, which applies unsupervised machine learning to reduce false positives and risk.


Protect your business, your customers, and your data.

Request Demo