Real-time Decisions. End-to-end Workflows. Open Platform.
Early detection of fraudulent account opening requests or loan applications.
Stop fraudulent and unauthorized ACH, wires, ATM withdrawals, and check fraud.
Identify fraudsters using stolen credit cards or other payment methods; prevent chargebacks.
Built to process massive amounts of digital data in real time to enhance detection accuracy and enable rapid response in a single, multi-tenant enterprise deployment.
Leading with the Unsupervised Learning approach, DataVisor enables early detection and adaptive response to new and evolving fraud attacks without the need for historic fraud labels. The platform also provides the added benefit of rules generation and supervised models for holistic protection.
Robust UI enabled guided workflows, dynamic update to black/white lists and graph analytics empower analysts to monitor business risks and policy violations with ease and take action with confidence.
Leading money transfer institution uses DataVisor to fight fraud in real-time with less than 1% false positives.
3 fast growing digital marketplaces saved millions in fraud losses while realizing substantial operational efficiencies and delivering a frictionless customer experience.
One of the world’s best established cryptocurrency exchanges spearheading the next generation of decentralized finance uses DataVisor to stop fraudsters from abusing promotions intended for customer acquisition during its aggressive growth phase.
Leading US retailer uses DataVisor Identity Graphs to stitched together all their customer data to have a single and complete view of all users and their connections to others.
A top global payment solution provider had limited ability to keep up with rapidly changing fraud tactics. Decaying detection models, incomplete data and lack of a modern infrastructure to support real-time detection at scale were putting them at risk. DataVisor’s comprehensive, AI-driven fraud and risk solutions accelerated model development by 5X, delivering early detection at scale.