Are You Struggling with These Merchant Risk Management Challenges?
Optimize risk management by eliminating costly chargebacks, manual inefficiencies, and false positives, while ensuring scalability and seamless operations.
Unmanaged Merchant Risk
One suspicious merchant can push chargeback ratios above card-network thresholds, creating fines, frozen reserves, and reputational damage before teams even notice the surge.
Manual Monitoring Processes
Analysts pivot between spreadsheets, legacy dashboards, and emailed alerts, delaying decisions and letting fast-moving fraud drain margins in real time.
High False Positives
Rigid, rule-only engines decline good transactions, driving merchants to rival processors and inflating customer-service costs.
Scalability Challenges
Seasonal volume spikes and new payment rails overwhelm static systems, leaving risk teams blind to anomalies once volumes exceed planned capacity.
Transform Merchant Risk with FraudNet Solutions
FraudNet empowers payment processors with seamless risk management, reducing fraud and protecting revenue effortlessly.
FraudNet Real-Time Analytics
Live scores every transaction, surfacing risky merchants instantly.
FraudNet ML Scoring Engine
Adaptive models slash false positives without relaxing protection.
FraudNet Unified Dashboard
Consolidates data, automates alerts, ends spreadsheet chaos.
FraudNet Elastic Cloud Scale
Auto-scales to peak volumes, keeping detection latency low.
Millisecond Decisioning
Experience AI-driven risk assessment in milliseconds, empowering you to intercept fraudulent activities before transaction authorization completes. Safeguard genuine sales and enhance merchant relationships with precise, rapid decision-making that keeps your operations smooth and your clients satisfied.
360° Merchant Intelligence
Gain unparalleled insights into merchant health with global consortium data, device signals, and behavioral analytics. Equip your payment processing team to predict and prevent risks, ensuring smoother transactions and enhanced trust. Stay ahead by understanding every merchant's unique profile and behavior.
Configurable, Low-Code Rules
Empower your team with configurable, low-code rules that adapt swiftly to emerging fraud schemes. Seamlessly implement policy changes without depending on lengthy IT processes, ensuring you stay ahead in the fast-paced world of payment processing and fraud prevention.
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 real-time analytics in payment processing?
Real-time analytics in payment processing refers to the immediate analysis and processing of transactional data as it occurs. This approach enables payment processors to monitor transactions, detect fraud, and ensure compliance instantaneously. By leveraging real-time analytics, businesses can make informed decisions quickly, enhancing their ability to respond to issues and optimize transaction processing efficiency.
Why is real-time analytics important for payment processors?
Real-time analytics is crucial for payment processors because it enhances fraud detection, improves transaction approval rates, and ensures better customer experiences. By analyzing data instantly, payment processors can identify suspicious activities and respond to them immediately, reducing the risk of fraudulent transactions. Additionally, it allows for dynamic optimization of transaction routing, leading to faster and more reliable payment processing.
How does real-time analytics improve fraud detection?
Real-time analytics improves fraud detection by continuously monitoring transactions for patterns and anomalies that indicate potential fraud. By leveraging machine learning algorithms and historical data, real-time systems can flag suspicious activities as they happen, allowing payment processors to intervene promptly. This proactive approach reduces the likelihood of fraudulent transactions going unnoticed and helps in minimizing financial losses and chargebacks.
What challenges do payment processors face with real-time analytics?
Payment processors face several challenges with real-time analytics, including data integration from multiple sources, ensuring data accuracy, and maintaining system performance under high transaction volumes. Additionally, implementing effective machine learning models for fraud detection requires significant computational resources and expertise. There is also a need for robust data security measures to protect sensitive information from breaches during real-time processing.
What technologies are commonly used in payment processor real-time analytics?
Technologies commonly used in payment processor real-time analytics include big data platforms like Apache Kafka and Apache Spark for data streaming and processing. Machine learning frameworks such as TensorFlow and Scikit-learn are employed for building predictive models. Additionally, cloud computing services like AWS, Google Cloud, and Azure provide scalable infrastructure for handling large volumes of transactional data efficiently and securely.
How can real-time analytics enhance customer experiences in payment processing?
Real-time analytics enhances customer experiences by ensuring faster transaction approvals and reducing false declines. It enables personalized services, such as tailored offers and loyalty rewards, by analyzing customer behavior instantaneously. Additionally, real-time insights help in identifying and resolving issues promptly, minimizing disruptions and improving overall satisfaction. By providing seamless and secure payment experiences, businesses can foster customer trust and loyalty.