Are You Struggling with Unmanaged Risk and Inefficient Merchant Monitoring?
Enhance compliance, reduce fines, and streamline operations by effectively managing risk and monitoring merchants with precision.
Unmanaged Merchant Risk
Without continuous, granular oversight, high-risk MIDs slip through portfolio controls. Sudden refund surges or hidden bust-outs create compliance headaches and expose processors to network fines and reputational damage.
Manual Monitoring Bottlenecks
Analysts still lean on Excel and ad-hoc SQL pulls to trace merchant behavior. Slow, error-prone reviews delay action, inflate labor costs, and leave genuine merchants stranded in lengthy queues.
Chargeback Threshold Violations
Missing early warning signals for rising dispute ratios triggers Visa/Mastercard programs. Penalties, higher reserve requirements, and stressed acquirer relationships directly erode processor margins.
Excessive False Positives
Rigid, one-size-fits-all rules flag normal volume changes as fraud. Legitimate merchants face settlement holds, while support teams battle avoidable escalations and revenue leakage.
FraudNet Solutions: Elevate Merchant Risk Management Effortlessly
Streamline risk management and boost efficiency with FraudNet's tailored solutions for payment processors.
Real-Time Policy Engine
Real-time policy engine enforces merchant limits, cutting false alerts at scale.
ML Anomaly Detection
ML anomaly detection flags new fraud patterns without overblocking good merchants.
Merchant-Level Thresholds
Custom thresholds per MID lower noise, preserving revenue and partner satisfaction.
Unified Case Dashboard
Unified dashboard auto-routes cases, slashing review time and ops overhead.
Adaptive AI-Native Scoring
FraudNet swiftly adapts to each merchant's unique transaction patterns, scoring in milliseconds to minimize false declines. This ensures high approval rates across your processor portfolio, enhancing both merchant satisfaction and your bottom line by maintaining seamless, trustworthy payment experiences.
End-to-End Workflow Automation
Streamline your operations with integrated alerting, evidence gathering, and resolution tools. Manage cases from a single console, allowing your team to quickly triage, investigate, and close cases efficiently. Reduce operational costs and audit preparation time while enhancing your compliance capabilities.
Instant, Configurable Alerts
Set your risk, chargeback, and refund thresholds just once, and let FraudNet handle the rest. With real-time alerts and automatic actions—like pausing terminals or holding payouts—potential threats are swiftly contained, protecting your business before they become costly issues.
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 false positives in payment processing?
False positives in payment processing occur when legitimate transactions are incorrectly flagged as fraudulent by fraud detection systems. This can result in declined transactions, causing inconvenience to customers and potential revenue loss for merchants. Reducing false positives is crucial to maintaining customer satisfaction and ensuring smooth transaction processing.
Why is reducing false positives important for payment processors?
Reducing false positives is important because it helps enhance customer experience by ensuring legitimate transactions are approved seamlessly. High false positive rates can lead to customer frustration, lost sales, and damage to brand reputation. Moreover, it helps merchants avoid unnecessary operational costs associated with manually reviewing flagged transactions and supports maintaining a competitive edge in the market.
What strategies can be employed to reduce false positives?
To reduce false positives, payment processors can use advanced machine learning algorithms that continuously learn from transaction data to improve accuracy. Implementing multi-layered authentication processes, such as biometric verification, can also help. Additionally, fine-tuning fraud detection rules and thresholds, and using historical transaction data analytics to understand customer behavior patterns, are effective strategies.
How does machine learning help in reducing false positives?
Machine learning helps reduce false positives by analyzing vast amounts of transaction data to identify patterns and anomalies more accurately than traditional rule-based systems. It can adapt to new fraud tactics in real-time and provide more precise risk assessments, which minimizes the chances of legitimate transactions being flagged incorrectly. Over time, machine learning models improve their accuracy, leading to fewer false positives.
What role does customer data play in false positive reduction?
Customer data plays a crucial role in reducing false positives by providing context for transaction behavior. Detailed data, such as purchasing history, location, and device identifiers, helps create comprehensive customer profiles. This allows fraud detection systems to differentiate between regular customer behaviors and potential fraud, thereby reducing the likelihood of false positives. Ensuring data privacy and compliance is essential when using customer data.
Can collaboration between merchants and payment processors help reduce false positives?
Yes, collaboration between merchants and payment processors can significantly reduce false positives. By sharing insights and data on transaction patterns and fraud trends, both parties can refine fraud detection models and rules. This collaboration fosters a better understanding of legitimate customer behaviors and helps tailor fraud prevention strategies to specific business needs, ultimately reducing the rate of false positives.