Instant AI assessment of transactions and users, with anomaly detection that flags fraud before losses pile up.
97% fewer false positives80% fraud reduction20% more approvals
Your Fraud Filters Are Blocking Good Customers
FraudNet combines custom machine learning, a no-code rules engine and a global anti-fraud network to cut false positives by 97% while stopping 80% more fraud in real time.
Talk to a solutions advisor about your fraud and compliance stack.
Trusted by teams at
MastercardCitibankRivertyBokuNelnetArvatoBankjoyAcima
What it does
One platform, end to end
Detection, entity risk, compliance and case management working together instead of stitched together.
Real-time risk scoring
Instant AI assessment of transactions and users, with anomaly detection that flags fraud before losses pile up.
No-code rules engine
Business users create and modify fraud rules without technical expertise, so you adapt to new schemes in hours.
Custom AI models
Supervised Machine Learning, Graph Neural Networks and Generative AI trained on your data for your risk profile.
Learning Loop
Outcomes feed back into the models continuously, so detection accuracy improves as fraud tactics change.
Global Anti-Fraud Network
Collective intelligence shared across the platform's user base, giving you fraud pattern data beyond your own book.
Compliance suite
AML and KYC verification, entity screening and transaction monitoring built into the same workflow.
Flexible dashboards
Customizable analytics and reporting with real-time insights for fraud, risk and compliance teams.
Case management
End-to-end workflow management for fraud investigations, from alert to resolution.
97%reduction in false positives
80%reduction in fraud
20%boost in approval rates
How it works
From raw signal to decision in one pass
From first touch to real results, without the guesswork.
Ingest
Collect real-time transaction and user data through APIs and SDKs.
Enrich
Add signals from the Global Anti-Fraud Network and third-party sources.
Analyze
Graph Neural Networks and Generative AI models analyze patterns and entity relationships.
Decide
ML outputs combine with the no-code rules engine to generate risk scores in real time.
Learn
The Learning Loop feeds outcomes back into the models to keep accuracy climbing.
What teams see
What teams say after switching
“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.”
FAQ
Questions fraud and risk teams ask us
What results can we expect?+
Companies typically see a 97% reduction in false positives, an 80% reduction in fraud, and a 20% boost in approval rates.
Do we need engineers to manage the rules?+
No. The no-code rules engine and flexible dashboards are built for business users, while custom ML models handle the heavy analysis.
How does the Learning Loop improve detection over time?+
It continuously feeds outcomes back into the models, incorporating new data and patterns so detection accuracy keeps improving.
What compliance capabilities are included?+
AML and KYC verification, entity screening, transaction monitoring and case management, all integrated with the fraud detection workflow.
Which industries is FraudNet built for?+
Payments, Financial Services, Fintechs and Commerce, with customization for each industry's risk profile.
How does the Global Anti-Fraud Network work?+
It pools fraud patterns and insights across the platform's user base, so every participant benefits from intelligence beyond their own data.
How do we get pricing?+
Pricing is customized to your requirements and scale. Book a call and a solutions advisor will scope it with you.
Get started
See what 97% fewer false positives looks like on your data
Book a call and a solutions advisor will walk through your fraud, risk and compliance stack.
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