Is Your Business Struggling with These Critical Payment Challenges?
Address critical payment challenges head-on, safeguarding your margins and enhancing customer trust with seamless fraud prevention and compliance solutions.
High Fraud in RTP & Cross-Border Flows
Instant settlement means you can’t manually review transactions. Losses post-authorization directly reduce margin and expose you to network fines.
Account Takeovers & Synthetic IDs
Fraudsters hijack customer logins or create fake personas, draining wallets and triggering costly reimbursements under consumer-protection rules.
Soaring Chargebacks and Disputes
Card-not-present abuse and promo fraud inflate refund rates, driving up interchange claw-backs and operational expenses.
Fragmented Global Compliance
Different AML, KYB, and sanctions rules by region force you to juggle siloed tools, increasing audit risk and overhead.
FraudNet Solutions: Combat Fraud and Ensure Seamless Security
Boost efficiency and safeguard revenue with FraudNet's comprehensive solutions for payment companies.
Real-Time Transaction Monitoring
Score every payment in milliseconds; stop fraud before funds move.
Continuous Entity Screening
Automate AML, KYB, and sanctions checks at scale.
AI-Native Risk Decisioning
Self-learning models cut fraud without adding friction.
Centralized Case Management
One workspace unifies alerts, evidence, and workflows.
Millisecond-Level Detection
FraudNet's AI-Native engine scrutinizes thousands of signals in milliseconds, empowering payment companies to swiftly approve legitimate transactions while intercepting fraudulent ones before authorization. Enhance your security, protect margins, and deliver seamless experiences to genuine customers with unparalleled precision.
Unified Fraud & Compliance Hub
Streamline your operations by managing fraud alerts, chargebacks, AML cases, and sanctions hits all in one intuitive dashboard. This centralized approach eliminates the hassle of juggling multiple tools, slashing investigation time by up to 60% and enhancing efficiency.
Adaptive Models Trained on Your Data
Harness the power of machine learning tailored to your payment ecosystem. Our adaptive models learn from your transaction patterns, minimizing false positives and safeguarding revenue, while ensuring legitimate users enjoy a seamless, friction-free experience. Elevate your fraud prevention strategy with precision and efficiency.
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. By employing advanced algorithms and machine learning techniques, these systems can detect anomalies and patterns that indicate fraudulent activities. This allows payment companies to proactively address potential threats and minimize financial losses, while also safeguarding customer trust and maintaining compliance with industry regulations.
How does machine learning enhance fraud detection in payment systems?
Machine learning enhances fraud detection by analyzing vast amounts of data to identify patterns and anomalies indicative of fraudulent behavior. It continuously learns from new data, improving its accuracy over time. This adaptive capability allows payment companies to detect emerging fraud trends and prevent them in real-time. Machine learning models can also reduce false positives, ensuring legitimate transactions are not unnecessarily flagged, enhancing customer experience while maintaining robust security.
What is the role of artificial intelligence in end-to-end fraud management?
Artificial intelligence (AI) plays a crucial role in end-to-end fraud management by automating the detection and prevention processes. AI systems can quickly analyze large datasets to identify suspicious activities, streamline decision-making with predictive analytics, and implement real-time responses to potential threats. Additionally, AI helps in recognizing complex fraud schemes that human analysts might miss, allowing payment companies to stay ahead of fraudsters and maintain secure transaction environments.
How can payment companies balance security and customer experience?
Payment companies can balance security and customer experience by implementing multi-layered security measures that do not overly disrupt the user's journey. Techniques such as behavioral biometrics, adaptive authentication, and real-time monitoring allow for secure yet seamless transactions. Regularly updating fraud detection algorithms to minimize false positives ensures customers are not unnecessarily inconvenienced. Additionally, transparent communication about security measures can enhance customer trust and satisfaction.
What are some best practices for implementing an end-to-end fraud management system?
Best practices for implementing an end-to-end fraud management system include using a combination of rule-based and machine learning models to ensure comprehensive coverage. Regularly updating and testing these systems to adapt to new fraud tactics is essential. Integrating real-time monitoring and alerts helps in swift response to threats. Collaboration with industry peers and sharing intelligence can enhance the system's effectiveness. Finally, training staff on fraud trends and system capabilities ensures robust defense mechanisms.
Why is real-time monitoring important in preventing payment fraud?
Real-time monitoring is crucial in preventing payment fraud as it allows for immediate detection and response to suspicious activities. By continuously analyzing transactions as they occur, payment companies can identify and block fraudulent attempts before they lead to financial losses. This proactive approach not only protects the company's assets but also minimizes the impact on customers, maintaining trust and reducing the likelihood of long-term damage to the company's reputation.