DataVisor
Unsupervised ML for Emerging Fraud Patterns
DataVisor uses unsupervised machine learning to detect emerging and unknown fraud patterns without relying on labeled training data. Their correlation engine clusters malicious accounts and behaviors in real-time by finding patterns that supervised ML models miss — especially effective for catching organized attack groups before they cause significant losses.
At a glance
Built for
Banks · Fintechs · Social Media · E-commerce
Based in
Mountain View, CA
Founded
2013
Official source
datavisor.comProfile snapshot
The essentials at a glance
A concise overview of where DataVisor fits in the financial crime technology landscape.
Category
Fraud Platform
Customer focus
Banks, Fintechs, Social Media, E-commerce
Headquarters
Mountain View, CA
Typical deployment
4–8 weeks
Capabilities and implementation
What this vendor profile covers
Use these published details to understand the vendor’s broad scope and implementation surface before moving into personalized analysis.
Directory detail
Public capabilities
- Unsupervised ML
- Emerging Fraud
- Account Fraud
- Correlation Engine
- No Labels Needed
Directory detail
Deployment options
- Cloud / SaaS
- On-Premise
- API
Directory detail
Common integrations
- REST API
- Kafka / Streaming
- Custom integrations
Directory detail
Trust and support details
- SOC 2 Type II
- ISO 27001
- Dedicated CSM
- Documentation
- Professional Services
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