DataVisor
Overview
DataVisor is an AI-powered fraud detection platform that uses unsupervised machine learning to detect fraud patterns without requiring labeled training data. This is particularly valuable for marketplaces, where new fraud schemes emerge constantly and traditional rule-based systems lag behind. DataVisor can detect coordinated fraud attacks, fake accounts, and promotional abuse at scale.
Best for: Large marketplaces facing sophisticated, coordinated fraud that traditional rule-based systems can't catch.
Key features
- Unsupervised machine learning
- Coordinated attack detection
- Fake account prevention
- Promotional abuse detection
- Real-time and batch processing
- Visual investigation tools
- Custom model training
Pricing
Model: Enterprise licensing
Pros & cons
Pros
- + Unsupervised ML — detects unknown fraud patterns automatically
- + No labeled data required to start detecting fraud
- + Strong at detecting coordinated attacks and rings
- + Handles promotional abuse and fake account creation
- + Scales to billions of events
Cons
- − Enterprise pricing — not accessible for small marketplaces
- − Complex integration and onboarding
- − Requires data science knowledge to maximize value
- − Less marketplace-specific than Sift
Related tools
Sift
Trust & SafetyGrowing marketplaces that need enterprise-grade fraud prevention across payments, accounts, and content.
Unit21
Trust & SafetyMarketplaces handling financial transactions that need regulatory compliance (KYC, AML) with minimal engineering overhead.
Incognia
Trust & SafetyMarketplaces with location-sensitive transactions (local services, delivery, ride-sharing) needing fraud prevention.
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