Verosint provides real-time, intelligent and automated fraud detection and prevention in the battle against persistent account fraud. With Verosint, online businesses can recognize and streamline access for legitimate customers, while blocking or challenging access by suspicious actors.
New Account Fraud
Onboard new customers with confidence while fighting one of the fastest growing types of online fraud – new account fraud.
Detect and prevent bot attacks, fake accounts, and synthetic accounts.
Stop fraudsters at the point of registration to prevent banking or credit card fraud.
Block duplicate accounts intended to abuse sign-up, referral, and free trial bonuses.
Protect your customers by preventing fraudsters from using stolen credentials to break into your legitimate customer accounts.
Analyze the risk of account profile changes and use rules to prevent account takeovers via email and phone number changes.
Block fraudsters before they can fraudulent purchases, withdraw funds, or disrupt your platform.
Protect customers from being blindsided by stolen credentials and maintain their trust in your platform and brand.
Identify when a single account is being shared by more than one person enabling you to proactively address revenue loss.
Analyze device, user, and account activity and spot patterns that indicate a shared password.
Take action to mitigate account sharing by requiring extra steps when a duplicate login is detected, such as generating an offer to upsell the customer to a paid account.
Get historical views of your account sharing events and track improvements over time.
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See Verosint in Action
Request a live demo to see how we can help you stop account fraud before it happens.
Whether you’re ready to get ahead of account takeover attacks, stop new account fraud in its tracks or ensure only the right people get access to your applications and systems, Verosint can help.
Learn how you can use Verosint to prevent account fraud
Get a risk report of your authorized users
See how we deliver actionable insights in real-time