You already know how to respond to ATO fraud damage. But what if you could stop it from even happening?
ATO Module can stop an account takeover in its tracks at the login attempt and provide human-readable explanations of the ML models’ reasoning to your team.
The solution is frictionless customer account defense with ATO Module
Fraudsters love to use automation tools to attack customer accounts, which are often “secured” with weak passwords. Maybe it’s time to invest in powerful, invisible ML defense of accounts so that your customers can focus on buying.
Follow our timeline
Step 1
User logs in to your environment. Countdown begins.
Step 2
We gather information about how the user keyed in the login credentials for the present analysis. What was the speed of the keystrokes? How does the left hand compare with the right hand? What about the mouse movement? We store the info for future reference and comparison.
Step 3
Your user's session is compared with all of the user's previous sessions looking at their attributes. It’s a combination of behavioral biometrics and the “cookie hijacking model.”
Step 4
After 1 second, we will have evaluated hundreds of attributes. After 2 seconds, it’ll be thousands.
Step 5
A graph of networks is built by matching transactions using shared attributes’ values. If it’s an account takeover, a picture develops. The probability that the user is a fraudster is calculated.
Step 6
3 seconds later, human readable and comprehensible recommendations appear in Nethone Panel. No inscrutable “black box” here – this is explainable AI.