Are High False Positives and Manual Reviews Draining Your Resources and Merchant Relationships?
Optimize your operations by reducing false positives and manual reviews, enhancing merchant relationships and resource efficiency.
High False Positive Rates
Legacy rules flag too many good transactions, forcing Acquirers to decline legitimate sales, hurting merchant relationships and network approval ratios.
Manual Review Overload
Fraud teams sift through thousands of alerts across disjointed tools, delaying authorizations, inflating headcount, and exposing the business to SLA breaches.
Merchant Friction and Churn
Frequent false declines trigger chargeback disputes and lost sales, driving merchants to seek rival Acquirers with higher acceptance rates.
Margin Erosion From Operating Costs
Excessive investigations, chargeback fees, and write-offs compress interchange margins and limit funds available for growth initiatives.
Transform Fraud Prevention with FraudNet's Cutting-Edge Solutions
Boost efficiency and merchant satisfaction by drastically reducing false positives and manual review workloads.
Real-Time Risk Scoring
Scores each authorization in milliseconds, cutting false positives by up to 98%.
Automated Alert Triage
Routes only high-risk cases to analysts, reducing reviews by 90%.
No-Code Rule Engine
Effortlessly create or update rules to keep up with new fraud patterns, no coding required.
Unified Case Console
Combines all evidence in one view, boosting analyst speed and accuracy.
Significant False-Positive Reduction
FraudNet’s AI-Native models meticulously evaluate millions of transaction signals, ensuring genuine payments are approved. This powerful precision not only safeguards merchant revenue but also strengthens your portfolio by minimizing fraud risk, enhancing trust, and bolstering long-term partnerships.
Operational Efficiency at Scale
Streamline your operations with automated triage and a unified workspace, empowering your team to handle increased transaction volumes efficiently. Reduce analyst costs, minimize manual interventions, and consistently meet stringent SLA targets, enhancing your service delivery and driving operational excellence.
Merchant Trust and Retention
Boost your merchant relationships and portfolio strength with higher approval rates, quicker authorizations, and significantly reduced chargebacks. Enjoy increased merchant satisfaction, loyalty, and lucrative interchange growth, all while minimizing churn and elevating your competitive edge in the market. Secure your success today.
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 is an acquirer false positive in payment processing?
An acquirer false positive occurs when a legitimate transaction is incorrectly flagged as fraudulent by the acquirer's fraud detection systems. This can result in the rejection of valid transactions, potentially leading to customer dissatisfaction, lost sales, and damaged relationships with merchants.
Why is reducing false positives important for acquirers?
Reducing false positives is crucial for acquirers because high false positive rates can lead to poor customer experiences, lost revenue for merchants, and increased operational costs. If legitimate transactions are frequently declined, it can also harm the acquirer's reputation and trust with both merchants and customers.
What are common causes of false positives in fraud detection?
Common causes of false positives include overly strict fraud detection rules, outdated algorithms that don't account for new transaction patterns, lack of real-time data analysis, and insufficient historical data. These factors can lead to the misclassification of legitimate transactions as suspicious.
How can acquirers reduce false positives in their fraud detection systems?
Acquirers can reduce false positives by implementing machine learning models that adapt to new fraud patterns, using real-time data analytics, continuously updating their fraud detection rules, and incorporating advanced technologies like behavioral biometrics and artificial intelligence to enhance accuracy in transaction evaluation.
What role does machine learning play in reducing false positives?
Machine learning helps reduce false positives by analyzing large datasets to identify patterns and anomalies that distinguish legitimate transactions from fraudulent ones. These models learn and adapt over time, improving their accuracy and reducing the likelihood of misclassifying genuine transactions as fraudulent.
How do acquirers balance fraud prevention with customer experience?
Acquirers balance fraud prevention with customer experience by employing risk-based authentication, which adjusts security measures based on the transaction's risk level. They also use data analytics to refine their fraud detection algorithms and work closely with merchants to ensure that security measures do not overly inconvenience or frustrate customers.