Custom AI models
Graph Neural Networks, Generative AI, and supervised machine learning work together to recognize sophisticated fraud patterns and entity relationships.
FraudNet combines Graph Neural Networks, Generative AI, and a Global Anti-Fraud Network to detect threats in real time. Built for payments, fintech, and financial services teams who cannot afford to get risk wrong.
Talk to our team about your fraud and compliance challenges.
Trusted by teams at
What it does
From data ingestion to decision orchestration, FraudNet handles the full fraud lifecycle without stitching together multiple vendors.
Graph Neural Networks, Generative AI, and supervised machine learning work together to recognize sophisticated fraud patterns and entity relationships.
Business users create and modify fraud detection rules without technical expertise, enabling quick adaptation to emerging fraud schemes.
Collective intelligence shared across the platform user base gives you fraud pattern data far beyond your own transaction history.
Outcomes feed back into the models continuously, so detection accuracy improves as new fraud patterns emerge and your business scales.
Customizable analytics and reporting interfaces deliver real-time insights so your team can monitor risk and respond immediately.
End-to-end workflow management for fraud investigations and resolution tracking, keeping your team organized and accountable.
Screen and monitor entities across your ecosystem to catch risk before it reaches your transaction flow.
Integrated AML and KYC verification tools handle regulatory requirements alongside fraud detection, no separate vendor needed.
Why change
Too many false positives kill customer trust. Too many missed threats kill revenue. FraudNet closes both gaps.
The old way
With FraudNet
Versus the old way
Step by step
A simple route from setup to steady output.
Real-time transaction and user data flows in through APIs and SDKs, then gets enriched with signals from the Global Anti-Fraud Network and third-party sources.
Graph Neural Networks and Generative AI models analyze patterns and relationships between entities to surface anomalies and coordinated fraud.
The decision engine combines ML model outputs with your no-code rules to generate a risk score for every transaction and user in real time.
The Learning Loop feeds outcomes back into the models, continuously refining detection accuracy as fraud tactics evolve.
Packages
Pricing is tailored to your transaction volume, industry, and compliance needs. Book a call to get a quote specific to your business.
Full platform access with custom AI models, Global Anti-Fraud Network, compliance suite, and dedicated support. Pricing based on your specific requirements and scale of operations.
Questions
FraudNet is an enterprise-level fraud and risk management platform that combines AI-powered solutions for fraud detection, compliance, and risk management with a no-code rules engine and real-time monitoring.
The Learning Loop continuously adapts and improves detection accuracy by incorporating new data and patterns, using supervised machine learning and advanced AI to enhance fraud prevention over time.
Companies typically experience a 97% reduction in false positives, an 80% reduction in fraud, and a 20% boost in approval rates.
FraudNet primarily serves Payments, Financial Services, Fintechs, and Commerce industries with customized fraud prevention and risk management solutions.
FraudNet uses Supervised Machine Learning, Graph Neural Networks, and Generative AI for advanced fraud detection and risk assessment.
No. FraudNet features a low-code/no-code rules engine and flexible dashboards, making it accessible for users without technical expertise while maintaining powerful capabilities.
FraudNet offers AML and KYC verification, entity screening, and transaction monitoring as part of its integrated compliance suite.
Take the next step
Book a call with our team to discuss your fraud detection, risk management, and compliance needs.
Book a call