Ingest and enrich
Collect real-time transaction data through APIs and enhance it with signals from the Global Anti-Fraud Network.
FraudNet applies custom machine learning and a global anti-fraud network to cut false positives by 97% and reduce fraud by 80% without adding customer friction.
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The flow
Start fast and see the difference within weeks.
Collect real-time transaction data through APIs and enhance it with signals from the Global Anti-Fraud Network.
Graph Neural Networks and Generative AI analyze patterns and relationships between entities.
The decision engine combines ML outputs with your no-code rules to generate an immediate risk score.
The Learning Loop system feeds outcomes back into the models to continuously refine detection accuracy.
Proof
“FraudNet flexibility has helped our AfterPay business grow by allowing us to meet our increasingly complex customer and country requirements.”
“FraudNet's combination of customized machine learning and flexible rules management has been transformative.”
Side by side
Plans
Pricing is tailored to your specific requirements and transaction volume. Contact our team for a custom quote.
Custom
Tailored fraud prevention and risk management for your business.
Answers
FraudNet is an enterprise-level fraud and risk management platform that combines AI-powered tools for comprehensive fraud detection, compliance, and risk management with features like a no-code rules engine and real-time monitoring.
The Learning Loop system continuously adapts and improves detection accuracy by incorporating new data and patterns, utilizing supervised machine learning and advanced AI technologies.
Companies typically experience a 97% reduction in false positives, 80% reduction in fraud, and a 20% boost in approval rates.
FraudNet primarily serves Payments, Financial Services, Fintechs, and Commerce industries with customized tools.
No, FraudNet features a low-code/no-code rules engine and flexible dashboards, making it accessible for users without technical expertise.
Next step
Book a call to see how FraudNet can fit into your existing stack.
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