FraudNet's AI fraud platform cuts false positives by 97% while reducing fraud by 80%. Real-time risk scoring, a no-code rules engine, and a Global Anti-Fraud Network in one system.
Talk with a fraud specialist about your current false positive and fraud loss rates.
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The shift
Legacy detection flags honest customers, misses new fraud patterns, and burns your analysts' time.
The old way
The FraudNet way
The flow
A clear path from first step to measurable outcome.
Collect real-time transaction and user data through APIs and SDKs.
Add signals from the Global Anti-Fraud Network and third-party sources to every event.
Graph Neural Networks and Generative AI models analyze patterns and relationships between entities.
ML outputs combine with the no-code rules engine to generate risk scores and real-time decisions via APIs and webhooks.
The Learning Loop feeds outcomes back into the models so accuracy keeps improving.
What you get
Detection, compliance, and case management working from the same real-time data.
Instant AI assessment of transactions and users, with anomaly detection that flags threats the moment they appear.
Business users create and modify fraud rules without technical expertise, so you adapt to new patterns in hours, not sprints.
Collective intelligence pooled across the FraudNet user base, giving you fraud pattern data far beyond your own experience.
Graph Neural Networks, Generative AI, and supervised machine learning reveal relationships and patterns conventional tools miss.
Detection accuracy improves continuously as outcomes feed back into the models, keeping pace with evolving fraud tactics.
Integrated AML and KYC verification, entity screening, and transaction monitoring in one place.
Customizable analytics and reporting interfaces with real-time insights for fraud and risk teams.
End-to-end workflow management for fraud investigations, from alert to resolution.
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.”
Common questions
Companies implementing FraudNet typically see a 97% reduction in false positives, an 80% reduction in fraud, and a 20% boost in approval rates.
No. The platform features a low-code/no-code rules engine and flexible dashboards, so business users can build and adjust fraud rules without engineering support.
The Learning Loop continuously incorporates new data and outcomes back into the models, using supervised machine learning to improve detection accuracy over time.
FraudNet includes AML and KYC verification, entity screening, and transaction monitoring as part of the platform.
Payments, Financial Services, Fintechs, and Commerce, with customized fraud prevention and risk management for each.
It pools fraud patterns and insights across the FraudNet user base, so you benefit from threat intelligence gathered far beyond your own transaction data.
Move forward
Book a call and we will walk through your fraud, false positive, and approval rate challenges with a specialist.
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