Fraud Management for Retail and E-Commerce

Prevent promotion abuse, mass-registered fake accounts, and account takeover in real time. Eliminate fraud losses and provide great experiences to loyal customers.

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"DataVisor is cool for inverting this philosophy by putting the unsupervised machine learning approach in the forefront. Its clients benefit by being able to rapidly identify previously unseen fraud attacks and by not having to spend time and resources refreshing their fraud detection models regularly."

- Gartner Cool Vendors in Identity and Access Management and Fraud Detection

Continuous Protection for Your eCommerce Platform Throughout the Entire Customer Journey

Protect your platform and inspire trust by enabling seamless and secure commerce, from account creation to payments, shipping and reviews.

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Solutions for Every Fraud Type

Promotion Abuse

Account Takeover

Fake Accounts

Promotion Abuse

Prevent financial loss, preserve brand reputation, and ensure valuable promotions reach real customers.

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Account Takeover

Protect good customers by uncovering large-scale ATO attacks in real time, and safeguard existing accounts against new and emerging fraud.

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Fake Accounts

Proactively block the mass registration of fake accounts to prevent downstream financial loss, brand damage, and customer churn.

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Advanced Capabilities, Outstanding Performance

Scalability

Block fake buyers and sellers at large scale, and stop payment fraud. Track, detect, and prevent malicious actions initiated by bots, device farms, and human farms.

Unparalleled Accuracy

Predict and prevent promotion abuse and fraud attacks with 99%+ accuracy. Detect, deter, and prevent e-commerce fraud with consistency and confidence.

Real-Time Production Readiness

Deploy machine learning models to directly operate on production data. Detect new fraud attacks with no need for labels or historic data.

"With DataVisor and unsupervised machine learning, we were able to identify and stop mass-scale fraud attacks before they had any effect on our users."