Bot-powered credential stuffing attacks are coordinated, automated, and massive in scale. To prevent ATO of this type, advanced fraud management is required.
Synthetic identity theft - when a fraudster creates a composite identity from a mix of real and fake information and applies for loans with the identity - is a growing problem for financial institutions.
Fraudsters are constantly finding ways to commit fraud through the mobile channel. This post highlights the techniques and methods they use.
DataVisor's CEO Yinglian discusses the biggest trends in digital fraud from 2018 and makes predictions for what 2019 will bring.
DataVisor research insights on the rising wave of sophisticated fraud, proactive ways for fraud prevention and role of unsupervised machine learning
The holiday season provides fraudsters a perfect ground to attack. DataVisor’s Unsupervised Machine Learning can help buyers & sellers in marketplace.
This post provides a few details about synthetic identity fraud and S.B. 2155, including what businesses should expect when it comes to the rollout of the law.
Application fraud is sophisticated and legacy systems are unable to combat it. DataVisor’s Unsupervised Machine Learning identifies hidden attack patterns.