DataVisor, the world’s leading AI-powered fraud and risk platform, proudly announced that it has received two prestigious honors in the 2024 Fraud & AML Impact Awards by Datos Insights. DataVisor was recognized as the winner in the Best Joint AML and Fraud Transaction Monitoring Innovation category and the silver medalist in the Best Transaction Fraud Monitoring and Decisioning category for its next-gen platform powered by advanced artificial intelligence and machine learning. This is the second consecutive year DataVisor was recognized by Datos Insights and its panel of industry subject matter experts for its fraud monitoring and decisioning innovations in the Fraud & AML Impact Awards. Datos Insights’ annual awards recognize and honor the industry’s most impactful fraud and AML innovations. The Fraud & AML Impact Awards program identifies winners from a highly competitive field, with rigorous evaluation criteria including innovation, competitive advantage, market need, risk mitigation, customer experience, operational efficiency, and scalability.
According to Becki LaPorte, a Fraud & AML Strategic Advisor at Datos Insights, “DataVisor’s end-to-end platform offers an innovative approach in the battle against fraud and financial crimes. By leveraging AI and machine learning, it delivers real-time detection and monitoring across both fraud and AML domains. This integrated-platform solution addresses the industry’s increasing demand for more effective and efficient financial crime prevention strategies, adeptly managing the complexities of modern transactions and adapting to the evolving tactics of financial criminals.”
In its recently published report, Datos Insights recognizes several key features and notable client benefits shared by DataVisor in its submission. These position DataVisor’s platform as a standout in both the Joint AML and Fraud Transaction Monitoring Innovation category and the Best Transaction Fraud Monitoring and Decisioning category:
- Reduced Fraud Losses and False Positives: Clients report 60% less fraud loss, 5x early detection, and 50% higher approval rates; 50% fewer false positives in AML, 60% reduction in repeated sanction alerts.
- Increased Efficiencies: Client benefits include doubled AML investigator efficiency, 60% less manual work in CTR/SAR filing, and 80% reduction in manual case creation.
- Real-time Data Orchestration and Decisioning: Facilitates seamless, real-time transaction monitoring for early detection and prevention of fraud and money laundering.
- Comprehensive Functions and Coverage: Offers end-to-end fraud and compliance solutions, including all AML workflows and comprehensive fraud use cases.
- Patented Unsupervised Machine Learning Technology: Leverages unsupervised machine learning to detect emerging fraud and financial crimes without prior labels.
- Generative AI Integration: Boosts auto-rule tuning, feature script generation, and rule descriptions, improving detection effectiveness and lowering false positives.
- Extensive Platform Ecosystem: Integrates seamlessly with key signal vendors and customer communication solutions, expanding the scope of fraud and AML protection without additional integration efforts.
“With an increase in real-time transactions and more stringent AML regulations, the need for advanced and integrated technology to address both fraud prevention and AML compliance has never been more urgent,” said Yinglian Xie, CEO and Co-Founder at DataVisor. “We’re honored to be recognized as a leading platform in these prestigious industry awards. Our holistic platform dismantles silos, providing a seamless, unified view of customer activity that not only bolsters fraud detection but also ensures comprehensive AML compliance. With cutting-edge AI and machine learning at its core, our platform empowers financial institutions to stay ahead of financial crime by significantly reducing false positives and costs through greater operational efficiency. It also enables expert navigation of the increasingly intricate regulatory landscape with unparalleled agility and precision.”
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