Anti-Money Laundering

Monitor suspicious AML activities with advanced AI for financial services. Boost detection, accelerate decisions, reduce overhead, and maintain compliance.

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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 too often forced to choose between keeping costs down and risking high regulatory fines, or paying top dollar to stay compliant. DataVisor provides advanced machine learning-powered fraud solutions that can stop would-be attackers and sophisticated crime rings before they cause harm. Proprietary unsupervised machine learning algorithms detect hidden networks of suspicious activity by analyzing enormous quantities of data across accounts and customers.

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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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Structuring

Unsupervised machine learning algorithms look at complex networks of transactions instead of individual ones, and can detect and eliminate launderers who deposit small denominations of funds to avoid CTR reporting.

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Layering

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

Products

to Manage the Complete AML Risk Lifecycle

Augmentation and Automation

Catch sophisticated money launderers with the comprehensive fraud management solution that combines unsupervised machine learning algorithms with powerful enterprise workflows. Perform global network detection to holistically reveal money laundering patterns, while lowering false positives and ensuring operational efficiency.

Real-Time Detection

Detect hidden networks of money laundering activity with a robust fraud detection solution that combines adaptive machine learning technology and powerful investigative workflows to deliver real-time fraud analytics. Triage alerts effectively, and build a robust AML infrastructure to prevent reputational and financial damage.

Faster 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. Legacy models also require constant retuning as fraudsters learn and employ new techniques to avoid detection. The DataVisor approach is to take a holistic view of the relationships between accounts, to identify hidden patterns and catch cybercriminals in the act. This dramatically increases rates of detection and reduces the time and effort required for investigations. Our solutions also enable companies to meet strict compliance requirements by creating human-understandable rules.

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Improved Real-Time Detection

Adapt to new and evolving money laundering tactics and techniques; stop fraudulent activities in real time.

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Swift Investigations

Automatically receive linked accounts and suspicious attributes to accelerate investigations.

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Explainable Results

Bridge the gap between machine learning techniques and compliance requirements with human-understandable reasons.

Client Success Stories

Application Fraud Case Study with Leading U.S. Card Issuer

DataVisor partnered with a top U.S. credit card issuer to deliver a scalable solution to fight application fraud.

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Fighting Fraud with Machine Learning: Stories from the Frontline

5 stories. 5 victories against fraud. See how organizations across industries are proactively defeating attacks.

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Top Financial Institution Uses DataVisor UML Solution to Fight Fraudulent Transactions

Learn how financial institutions are successfully saving millions in the fight against fraud.

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