An Intelligent Approach to Incessant Attacks

From identity theft to the highly-creative synthetic identities, account fraud comes in all shapes and sizes.

It’s no secret that personal information is widely available and has long-enabled fraudsters to open accounts using stolen identities. And today, fraudsters use sophisticated techniques to create whole new synthetic identities seemingly from thin air. With no consumer victim to sound the alarm, synthetic identity fraud is almost the perfect crime and most often utilized.

 Our machine learning technology proactively detects and eliminates the most sophisticated online attacks without requiring extensive historic loss experience or training times.

Powerful Protection Starts with an Account

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Application Fraud

Fraudsters targeting financial services are technically savvy and adopt advanced techniques to cover their tracks from IP blacklists and rules-based systems. DataVisor’s early detection prevents fake accounts from being opened with an intent to commit fraud and/or other malicious activities.

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Mass Registration

Fraudsters leverage free email services to mass register seemingly-authentic accounts to either unleash their own attacks, or to sell to other fraudsters. Unsupervised machine learning takes a holistic view of all account registrations, identifying correlated attack behaviors to prevent large scale fake registrations.

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Account Takeovers

Fraud-as-a-service economy with compromised accounts are sold or exchanged for a variety of downstream attacks, and since they are created by real users, they can often evade security solutions. With continuous monitoring of all accounts, Datavisor proactively surfaces modern fraud attacks.

DataVisor. Driven by Accuracy.​

DataVisor Enterprise analyzes suspicious applications and accounts simultaneously to detect even the most tenuous connections between fraudulent assets, even when they appear legitimate in isolation. DataVisor puts a stop to fraud in real time at account approval, without the use of time-consuming training data or labels.

Accuracy and Coverage

Detects fraud attacks before they happen, achieving unrivaled detection accuracy and industry-leading coverage at the same time.

Proactive Detection

Detects moving targets – such as changing or new attack patterns – by exposing hidden connections between accounts without relying on training data or labels.

Improved Customer Experience

Driven by accuracy, allowing companies to identify good and bad users, reduce authentication measures, and streamline for an overall improved customer experience.

Ready to enhance your detection with unsupervised machine learning?