Is Merchant Risk Management Draining Your Resources?
Optimize your resources by automating merchant risk management, reducing operational costs, and protecting your reputation with card networks.
Unmanaged Merchant Risk
Intermittent monitoring lets bad actors exploit processor platforms, leading to surprise spikes in chargebacks, fines, and reputational damage with card networks.
Manual Monitoring Processes
Analysts juggle Excel sheets and legacy dashboards to track thousands of merchants, slowing reaction times and inflating operational costs as volumes grow.
Chargebacks & Threshold Violations
Unchecked breaches of refund, velocity, or fraud‐to‐sales ratios trigger scheme penalties and endanger sponsor-bank relationships.
High False Positives
Rigid rules flag legitimate merchants, freezing payouts, frustrating clients, and driving costly support escalations.
Empower Your Business with FraudNet's Cutting-Edge Solutions
Optimize resource allocation and protect revenue with FraudNet's intelligent merchant risk management solutions.
Policy Monitoring Engine
Real-time rule enforcement prevents merchant chargeback and refund breaches.
Anomaly Detection Models
ML models flag atypical merchant spikes missed by static, hard-coded limits.
Merchant-Level Threshold Customization
Granular, adjustable limits cut false positives without weakening fraud defenses.
Unified Case Management Dashboard
One queue for alerts, documents, and actions accelerates investigation closure.
Real-Time Policy Enforcement
FraudNet instantly stops out-of-policy transactions, keeping you compliant with network chargeback and fraud thresholds. Protect your revenue and reputation with milliseconds-fast enforcement, ensuring seamless operations and satisfied clients while safeguarding against financial penalties and maintaining trust with card networks.
Advanced Anomaly Detection
Harness the power of AI-Native models that understand typical merchant behavior, spotlighting only true threats. Reduce investigative noise by up to 70%, allowing your team to focus on genuine risks and maintain seamless payment processing to enhance client satisfaction.
Tailored Merchant Monitoring
Customize monitoring with FraudNet by setting specific limits for each MID, business vertical, or risk category. As transaction patterns evolve, FraudNet automatically adapts, significantly reducing false positives and minimizing client turnover, ensuring smooth operations and satisfied partners.
Impact & Results
Delivering Results that Matter
We don’t just promise better fraud control—we deliver tangible improvements that protect your business.
97%
Fewer False Positives
Approve more valid transactions confidently.
88%
Fraud Reduction
Experience double-digit reductions in fraud-related chargebacks
60%
Cost Savings
Save time and resources while securing your revenue.
Why FraudNet
Future-Proof Your Fraud & Risk Program
With an integrated platform designed for precision, agility, and impactful results, enabling your team to make smarter decisions, improve operational efficiency, and fuel your business growth.
Customizable & Scalable
No-code rules engine, flexible dashboards, and tailor-made machine learning models that are designed to adapt seamlessly and scale alongside your business.
End-to-End Platform
Unify fraud detection, compliance, and risk management into one powerful solution, saving valuable time and streamlining your operations.
AI Precision You Can Rely On
Reduce false positives, detect and prevent more fraud, and mitigate risk with highly accurate, real-time risk scoring and anomaly detection you can trust.
Real-Time Fraud Intelligence
Leverage advanced analytics, comprehensive reporting, and our Global Anti-Fraud Network to make faster, smarter decisions on the spot.
Testimonials
Real Success From Real Teams
Fraud.net’s flexibility has helped our AfterPay business grow by allowing us to meet our increasingly complex customer and country requirements. Their platform has enabled Arvato to increase our agility and significantly reduce fraud attacks.
Director Risk & Fraud, Arvato
FraudNet's combination of customized machine learning and flexible rules management has been transformative. We've achieved dramatic efficiency gains while maintaining robust fraud protection - a game-changer as we navigate evolving regulatory requirements.
Head of Financial Crime, Countingup
The great usability of Fraud.net is night and day when comparing it to our prior risk prevention platform. Reporting is also faster, more straightforward, and more impactful. With Fraud.net, we can easily visualize and share findings, providing our leadership with a clear understanding of the return-on-investment for our activities in real-time.
Fraud Manager, Global Financial Institution
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FAQs
What are adaptive fraud rules in payment processing?
Adaptive fraud rules are dynamic guidelines used by payment processors to detect and prevent fraudulent transactions. Unlike static rules, adaptive rules can adjust in real-time based on evolving fraud patterns and behaviors. This adaptability helps in identifying new threats as they emerge, improving the accuracy of fraud detection, and reducing false positives, which can enhance the overall security and efficiency of transaction processing.
How do adaptive fraud rules differ from traditional fraud detection methods?
Traditional fraud detection methods often rely on static rules and historical data, which may not adapt well to new or evolving fraud tactics. In contrast, adaptive fraud rules use real-time data analysis and machine learning to continuously update and refine themselves. This allows them to respond to new fraud patterns swiftly, offering more accurate detection and reducing false positives, thereby providing more robust protection against fraud.
Why are adaptive fraud rules important for payment processors?
Adaptive fraud rules are crucial for payment processors because they enhance the ability to detect and mitigate fraudulent activities in real-time. They provide a flexible and responsive approach to fraud prevention, reducing the risk of financial losses and reputational damage. By lowering false positives, they also improve customer satisfaction by minimizing transaction disruptions. This adaptability ensures that payment processors can maintain security as fraud tactics evolve.
How do adaptive fraud rules utilize machine learning?
Adaptive fraud rules leverage machine learning algorithms to analyze vast amounts of transaction data and identify patterns indicative of fraud. Machine learning models are trained on historical and real-time data, allowing them to recognize anomalies and evolving fraud tactics. These models continuously learn and adapt their criteria for fraud detection, improving accuracy over time and enabling the system to respond swiftly to new threats.
What role does data play in adaptive fraud detection?
Data is fundamental to adaptive fraud detection as it provides the raw material for analysis and learning. Large datasets allow machine learning algorithms to identify patterns and anomalies associated with fraudulent behavior. Real-time data feeds enable adaptive systems to update and refine their models continuously, adapting to new fraud tactics as they emerge. The quality, volume, and diversity of data directly impact the effectiveness of adaptive fraud detection systems.
Can adaptive fraud rules reduce false positives in fraud detection?
Yes, adaptive fraud rules are designed to reduce false positives by using more sophisticated analysis and learning methods. By continuously updating their models to reflect current fraud trends, these systems can distinguish between legitimate and suspicious transactions more accurately. This reduces the number of false alerts, ensuring that legitimate transactions are processed smoothly while maintaining a high level of security against actual fraudulent activities.