FraudNet combines real-time risk scoring, a global anti-fraud network, and custom AI models to stop fraud before it lands. Payments, fintech, and financial services teams see results in 90 days.
Talk to a solutions advisor about your fraud and compliance stack.
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The case for change
They block good customers and still miss the fraud that matters.
The old way
The FraudNet way
What it does
Detection, entity risk, and compliance working from the same data and the same models.
Instant AI assessment of every transaction and user, so fraud is stopped at the moment of attempt, not after the loss.
Business users create and modify fraud rules without technical expertise, so you adapt to new fraud patterns in hours, not sprints.
Models that analyze relationships between entities to surface fraud rings and coordinated schemes single-transaction tools miss.
Collective intelligence pooled across the FraudNet user base, giving you fraud pattern insight far beyond your own data.
Outcomes feed back into the models continuously, so detection accuracy improves as your business and fraud tactics change.
AML and KYC verification, entity screening, and transaction monitoring built into the same workflow as fraud detection.
Customizable analytics and reporting with real-time insight into risk trends, alerts, and team performance.
End-to-end workflow for fraud investigations and resolution tracking, closing the loop from alert to outcome.
Outcomes
“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.”
Good to know
Companies typically experience a 97% reduction in false positives, an 80% reduction in fraud, and a 20% boost in approval rates.
No. FraudNet features a low-code/no-code rules engine and flexible dashboards, so business users can build and adjust fraud rules without engineering support.
The platform uses Supervised Machine Learning, Graph Neural Networks, and Generative AI for fraud detection and risk assessment.
It pools fraud patterns and insights across the FraudNet user base, giving every participant collective intelligence beyond their own data.
AML and KYC verification, entity screening, and transaction monitoring are built into the platform alongside fraud detection.
Payments, Financial Services, Fintechs, and Commerce, with customized fraud prevention and risk management for each.
It continuously feeds outcomes back into the models, incorporating new data and patterns so detection accuracy keeps improving.
Take the next step
Book a call and a solutions advisor will map FraudNet to your fraud, risk, and compliance stack.
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