Are You Struggling with Unmanaged Risk, Manual Monitoring, and High False Positives?
Streamline risk management with automated solutions, reducing fraud exposure and boosting compliance and operational efficiency for payment processors.
Unmanaged Merchant Risk
Payment processors oversee thousands of merchants; sporadic checks let fraudulent storefronts persist, making it difficult to demonstrate proactive risk controls to regulators and banking partners.
Manual Monitoring Processes
Excel-based reviews force analysts to piece together transaction, refund, and dispute data. Slow look-backs hide real-time threats and create audit gaps that weaken claims of control effectiveness.
High False Positives
Rigid, one-size-fits-all rules flag healthy merchants, freeze settlements, and overwhelm analysts. Excess noise inflates false-positive rates cited in bank and card-network control assessments.
Policy Compliance Gaps
Late detection of chargeback or refund thresholds leaves processors outside scheme windows, inviting fines and sponsor-bank scrutiny that undermine proofs of robust merchant fraud controls.
Boost Fraud Control with FraudNet's Advanced Solutions
Streamline risk management, enhance fraud detection, and reduce false positives effortlessly with FraudNet.
Policy Monitoring Engine
Real-time chargeback, refund, and volume rule enforcement.
Anomaly Detection Models
ML flags outliers unseen by static rules, revealing emerging fraud.
Merchant-Level Threshold Customization
Unique limits per merchant reduce false positives and protect revenue.
Unified Case Management Dashboard
Single workspace accelerates investigations and audit reporting.
FraudNet Real-Time Detection
Experience lightning-fast scoring across all merchant transactions, intercepting suspicious activities before funds settle. Provide your partners with undeniable proof of proactive fraud management, enhancing your reputation and strengthening regulatory and banking relationships with unparalleled efficiency and security.
FraudNet Reduced False Positives
Our adaptive models intuitively learn each merchant's transaction patterns, ensuring genuine sales proceed smoothly while isolating potential threats. This significantly reduces review queues and operational costs, allowing you to deliver a seamless experience for your most valued merchants.
FraudNet Compliance Automation
Streamline your compliance efforts with automated audit trails, comprehensive KPI dashboards, and policy attestations. Simplify exams for card schemes, PCI, and sponsor banks, enhancing your credibility and reducing audit cycle times, so you can focus on driving business growth.
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 types of payment fraud can detection software identify?
Detection software can identify various types of payment fraud, including credit card fraud, account takeover, phishing attacks, identity theft, and transaction laundering. These systems use machine learning and rule-based algorithms to analyze transaction patterns, detect anomalies, and flag suspicious activities in real-time, allowing businesses to mitigate risks.
How effective are payment processors at preventing fraud?
The effectiveness of payment processors in preventing fraud can vary based on the sophistication of their fraud detection systems, the volume of transactions they handle, and their ability to adapt to emerging threats. Generally, advanced processors employ multi-layered security measures, including AI-driven analytics, to achieve high levels of fraud detection and prevention, reducing false positives and minimizing losses.
What role does machine learning play in payment fraud detection?
Machine learning plays a crucial role in payment fraud detection by analyzing large volumes of transaction data to identify patterns and anomalies that may indicate fraudulent activity. It allows systems to learn from past transactions, continuously improving their accuracy and ability to predict new fraud techniques. This helps in reducing false positives and enhancing the speed of fraud detection.
How do payment processors balance fraud prevention with user experience?
Payment processors balance fraud prevention with user experience by implementing intelligent risk-based authentication methods that apply additional checks only to high-risk transactions. They use machine learning to assess transaction risk levels in real-time, allowing most legitimate transactions to proceed smoothly while flagging suspicious ones for further review. This approach minimizes friction for most users while maintaining robust security.
What are common challenges in maintaining fraud control effectiveness?
Common challenges include keeping up with evolving fraud tactics, managing false positives that can disrupt legitimate transactions, integrating fraud detection systems with existing payment infrastructures, and ensuring compliance with regulatory standards. Additionally, balancing security measures with customer convenience and maintaining data privacy are ongoing concerns for payment processors.
How do real-time fraud detection systems work in payment processing?
Real-time fraud detection systems work by analyzing transaction data as it occurs, using algorithms and machine learning models to identify suspicious activities instantly. These systems assess factors such as transaction amount, frequency, geographic location, and historical behavior to determine the likelihood of fraud. They can flag or block transactions, alerting businesses to potential threats and allowing for immediate response.