The Future of Network Detection

The threat of money laundering between highly-coordinated networks of cyber-criminals is growing year over year. These intelligent attacks involve complex interactions between multiple accounts and players, and they often result in massive financial loss and reputational damage for companies across a host of industries. 
Today, companies are forced to walk a thin line – keep costs down and risk high regulatory fines, or pay top dollars to stay compliant. U.S. financial institutions alone spent an astonishing $8 billion on anti-money laundering compliance in 2017. 
DataVisor’s industry-leading machine learning model is the premier solution to stop would-be attackers and sophisticated crime rings before they cause harm. UML detects hidden networks of suspicious activity by looking at enormous quantities of data across accounts, customers, and time. Malicious patterns are spotted, and criminals are thwarted.

DataVisor. Always One Step Ahead.

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Mule Accounts

Early detection stops money-launderers from using stolen or synthetic identities to create fraudulent accounts to move and transfer funds. 
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Unsupervised Machine Learning approach detects and eliminates launderers who deposit small denominations of funds to avoid CTR reporting by looking at network of transactions instead of individual ones.

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Real time machine learning recognizes and puts a stop to fraudsters attempting to mask money flow by transferring funds across multiple mule accounts.

Fast Detection for Faster Investigations

Current solutions for AML monitoring evaluate risk at the transaction level. This is an outdated method that results in a high volume of alerts, particularly false positives. To make matters worse, these technologies are woefully inadequate as they require constant re-tuning as fraudsters learn and employ new techniques to avoid detection. 
DataVisor Enterprise for AML takes a holistic view at the relationship between accounts to identify hidden patterns and catch cybercriminals in the act. This dramatically increases detection of criminal activities and reduces the time and effort required for investigations. DataVisor also enables companies to meet strict compliance requirements by creating human-understandable rules. 
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Improved Real-Time Detection

Robust technology adapts to new and evolving money laundering tactics and techniques and ends fraudulent activities in real time. 

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Swift Investigations

Automatically provides investigators with linked accounts and suspicious attributes to accelerate investigations.
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Explainable Results

Bridges the gap between machine learning techniques and compliance requirements of human-understandable reasons.

Ready to enhance your detection with unsupervised machine learning?