A revolution in e-commerce fraud detection is occurring – with new tools, techniques, and strategies to combat card-not-present (CNP) fraud.
New research by the Mercator Advisory Group, published in a a report sponsored by Kount, reveals how dynamic fraud detection tools are combating e-commerce fraud with machine learning and artificial intelligence, behavioral biometrics, persistent identity, dynamic risk scoring, mobile device ID and persona linking.
“Card-not-present (CNP) fraud in e-commerce has become a highly productive and cost-effective endeavor for criminals,” the report states. “It can be launched from anywhere in the world under cover of virtual anonymity. Even the human element can be eliminated by tech-savvy fraudsters who use botnets to do their dirty work. Networks of private computers can be infected with malicious software without the owners’ knowledge and programmed to attempt CNP transactions using stolen credit card data.”
But fraud detection tools are catching up to criminals, says the report, creating new ways to combat intelligent fraud.
“Fraud detection and prevention tools are advancing from static to dynamic. Passive is giving way to active. Systems that utilize fraud history databases and points scoring systems for e-commerce fraud management are being supplemented by tools termed ‘Fraud Detection 2.0’.”
“These newer techniques strike at the heart of fraudsters’ attempts by neutralizing their main tactics. Fraudsters previously could simply change their angle of attack and quickly spoof static fraud defenses. They could use their highly automated systems to mimic transactions that looked legitimate to a merchant but were really fake because they used stolen payment card credentials. ”
The detailed report breaks down these attributes in turn, as well as providing insight for merchants on the dark web and the underground market for stolen data, and how to manage and implement merchant fraud strategies.
You can download your copy of the report from Kount by clicking here.
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