Are High False Positives and Manual Reviews Hurting Your B2B Payment Efficiency?
Enhance your B2B payment efficiency by reducing false positives and minimizing manual reviews, improving revenue and vendor relationships.
High False Positive Rates Drain Revenue
Over-aggressive rules mislabel legitimate ACH and wire transfers, delaying payouts, triggering costly re-processing fees, and eroding thin B2B margins.
Manual Reviews Slow Payables Workflow
Analysts chase good payments across ERPs and bank portals, inflating overhead and diverting attention from truly suspicious activity.
Supplier Friction Damages Relationships
Trusted vendors endure repeated verifications or declines, leading to shipment delays, strained terms, and eventual churn.
Security-UX Balance Is Hard at Scale
Multiple rails, cross-border rules, and large ticket sizes make tuning fraud models without hurting client experience complex.
Transform Payments with FraudNet's Precision Solutions
Enhance B2B payment efficiency by reducing false positives and automating manual reviews seamlessly.
AI-Native Precision Scoring
Learns B2B patterns, cuts false positives by up to 90%.
Real-Time Consortia Insights
Uses shared intel to spot anomalies unknown to your data.
Dynamic Risk-Based Routing
Adjusts auth steps only when risk spikes, not every payment.
Automated Case Orchestration
Prioritizes alerts, closes safe cases with zero touch.
Unified B2B Graph Intelligence
FraudNet seamlessly connects every buyer, supplier, and account in a global network, empowering B2B payment companies to confidently approve legitimate transactions and detect fraudulent entities before any funds are transferred, ensuring smooth operations and safeguarding your revenue stream.
Self-Optimizing Decision Engine
Our AI-Native models continuously adapt to your unique transaction patterns, dramatically reducing false positives. Say goodbye to manual rule adjustments and let your team concentrate on strategic risk management, enhancing efficiency and accuracy in your B2B payment processes.
No-Code Workflow Automation
Streamline your payment security with visual playbooks that automatically close low-risk alerts, seamlessly integrate high-risk cases into your ERP, and generate comprehensive audit logs, reducing review efforts by up to 70%—allowing your team to focus on strategic initiatives.
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
Speak with our Solutions Expert Today
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Recognized by Industry Analysts
Related Resources
Other Services
FAQs
What is a false positive in B2B payment processing?
A false positive in B2B payment processing occurs when a legitimate transaction is incorrectly flagged as fraudulent by a detection system. This can happen due to overly strict fraud detection rules or algorithms that fail to account for unique business transaction patterns. Reducing false positives is crucial for maintaining customer relationships and ensuring smooth business operations, as unwarranted transaction blocks can lead to delays and loss of trust.
Why is reducing false positives important in B2B payments?
Reducing false positives is critical in B2B payments because these transactions often involve large amounts and key business relationships. Frequent false positives can disrupt business operations, delay critical payments, and damage trust between partners. Moreover, they can increase operational costs due to the manual review process required to resolve these errors. Efficiently reducing false positives helps maintain seamless payment processes and strengthens business partnerships.
What are common causes of false positives in B2B payment processing?
Common causes of false positives in B2B payment processing include rigid fraud detection rules, lack of customization for unique business patterns, outdated data models, and insufficient integration of contextual business intelligence. Additionally, failure to update algorithms with the latest transaction data and trends can result in legitimate transactions being flagged incorrectly. Addressing these issues with advanced analytics and machine learning can help reduce false positives.
How can machine learning help in reducing false positives in B2B payments?
Machine learning can significantly reduce false positives in B2B payments by analyzing vast amounts of transaction data to identify patterns and anomalies more accurately. These models learn from past transactions and continuously update their algorithms to adapt to new fraud tactics. By distinguishing between legitimate and suspicious activities with greater precision, machine learning can help refine fraud detection systems and reduce the number of false positives, improving overall transaction accuracy.
What steps can businesses take to reduce false positives in their payment systems?
Businesses can reduce false positives by implementing advanced fraud detection systems that use machine learning and data analytics to understand transaction patterns better. Regularly updating these systems with the latest transaction data and fraud trends is crucial. Additionally, customizing fraud detection parameters to align with specific business models and engaging in continuous monitoring and review of flagged transactions can further minimize false positives, ensuring smoother payment processes.
How can involving customers in the fraud detection process help reduce false positives?
Involving customers in the fraud detection process can help reduce false positives by providing additional context and verification. By enabling customers to confirm or dispute flagged transactions through alerts or notifications, businesses can quickly validate legitimate activities. This not only enhances the accuracy of detection systems but also fosters trust and collaboration with customers, allowing them to play an active role in safeguarding their transactions and reducing unnecessary disruptions.