DataVisor is the leading big data fraud detection solution utilizing unsupervised analytics to identify malicious account campaigns before they conduct any damage to banks, consumer-facing web sites and mobile apps. Our unique approach to big data fraud detection does not rely on prior knowledge of attack patterns – “training data” in data science speak.
The rapid expansion of consumer-facing online services has led to an explosion of user accounts, ushering in the “billion user era”. Well-organized attack campaigns are using this growth to their advantage, creating armies of fake and compromised accounts to hide in the shadows and conduct fraud against banks, web sites and mobile apps. It is challenging for trust and safety teams to stay ahead of these fraudsters since rules and models need constant maintenance and are always reacting after the damage has been done. Our approach to big data fraud detection gives you a leg up.
Adapt faster to changing threats and new products by dramatically shrinking the time it takes to test and deploy new profiles, rules, and models. Using a unique cognitive computing approach, IBM Safer Payments profiles the behavior of any entity and delivers best-fit analytics interactively to fraud professionals. This proven technology is already protecting some of the world's largest and most complex payment portfolios. Outthink fraud by rethinking detection.
DataVisor is ranked 30th in Fraud Detection and Prevention while IBM Safer Payments is ranked 11th in Fraud Detection and Prevention. DataVisor is rated 0.0, while IBM Safer Payments is rated 0.0. On the other hand, DataVisor is most compared with ThreatMetrix and Sift Digital Trust and Safety, whereas IBM Safer Payments is most compared with SAS Fraud Management, IBM Trusteer, Fraud Hunting Platform, Featurespace ARIC Fraud Hub and IBM Financial Crimes Insights (FCI).
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