Are Legacy Systems Costing You Time, Money, and Customer Trust?
Streamline your fraud prevention to reduce costs, save time, and enhance customer trust with modern, efficient solutions.
High False-Positive Rates
Legacy rules flag too many good transactions, driving cardholder friction, dispute calls, and costly write-offs.
Siloed, Low-Quality Data
Issuer authorization logs, network feeds, and KYC records live in separate systems, hindering holistic risk scoring.
Slow Manual Investigations
Analysts stitch together evidence across tools, delaying decisions, missing fraud windows, and inflating labor spend.
Regulatory & Audit Pressure
Real-time SAR, Reg E/Reg Z, and PCI mandates require detailed, time-stamped proofs many issuers can’t instantly deliver.
Transform Fraud Prevention with FraudNet's Cutting-Edge Solutions
FraudNet streamlines processes, reduces costs, and enhances customer trust by modernizing fraud detection for issuers.
AI-Native Adaptive Scoring
Self-learning models cut false positives in real time.
Unified Data Fabric
Streams issuer, network, and device data into one view.
Automated Case Workflow
Pre-built queues triage, document, and escalate in seconds.
One-Click Compliance Reports
Instant SAR, Reg E, and audit exports satisfy regulators.
Real-Time, Millisecond Decisions
Experience the power of real-time fraud prevention. FraudNet evaluates each transaction in milliseconds, allowing you to block fraudulent activities without disrupting legitimate purchases. Protect your cardholders and reduce friction, all while maintaining seamless, genuine spending experiences for your customers.
Network-Wide Fraud Intelligence
Leverage insights from a vast network of issuers and merchants to detect emerging fraud patterns before they escalate. Our system's collaborative intelligence ensures you're always a step ahead, enabling proactive measures against threats, unlike isolated, outdated solutions. Stay protected with cutting-edge vigilance.
Configurable No-Code Rules
Empower your team to swiftly adjust thresholds, execute A/B tests, and implement new controls without the need for IT tickets or downtime. Enhance your fraud prevention strategies with agility and precision, ensuring seamless protection for your cardholders and your bottom line.
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 issuer real-time transaction monitoring?
Issuer real-time transaction monitoring is a process where financial institutions continuously analyze transactions as they occur to detect and prevent fraudulent activities. This involves using advanced algorithms and machine learning to assess the risk of each transaction based on patterns, user behavior, and other criteria. By monitoring transactions in real-time, issuers can quickly respond to potential threats, reducing financial loss and enhancing customer trust.
How does real-time transaction monitoring benefit issuers?
Real-time transaction monitoring offers several benefits for issuers, including the ability to detect and prevent fraud promptly, thus minimizing potential financial losses. It also enhances customer satisfaction by providing a secure transaction environment, reducing the chances of false positives that can lead to customer inconvenience. Additionally, it helps issuers comply with regulatory requirements by maintaining a robust monitoring system that can adapt to evolving fraud tactics.
What technologies are used in real-time transaction monitoring?
Real-time transaction monitoring employs a range of technologies such as machine learning, artificial intelligence, and big data analytics. These technologies help in identifying unusual patterns and anomalies that may indicate fraudulent activity. Machine learning models can be trained on historical data to predict future fraud trends, while AI can automate decision-making processes, enabling faster response times. Additionally, data analytics tools provide insights into transaction behaviors and risk factors.
How does machine learning enhance transaction monitoring?
Machine learning enhances transaction monitoring by enabling systems to learn from historical transaction data and improve detection accuracy over time. It can identify complex patterns and subtle anomalies that might not be apparent through traditional rule-based systems. Machine learning models continuously evolve, adapting to new types of fraud and reducing false positives. This adaptability ensures that issuers can maintain effective fraud prevention strategies even as fraudsters change their tactics.
What challenges do issuers face in implementing real-time transaction monitoring?
Issuers face several challenges when implementing real-time transaction monitoring, including the need for significant investment in technology and infrastructure. They must also ensure that their systems can handle large volumes of transaction data without compromising speed or accuracy. Balancing fraud prevention with customer experience is another challenge, as overly aggressive monitoring may lead to false positives. Additionally, staying ahead of evolving fraud tactics requires continuous system updates and staff training.
How do issuers manage false positives in transaction monitoring?
Issuers manage false positives by implementing advanced analytics and machine learning algorithms that improve the accuracy of fraud detection systems. By continuously refining these models with updated data, issuers can reduce the number of legitimate transactions flagged as fraudulent. Additionally, they may employ multi-layered authentication processes to verify suspicious transactions without disrupting the customer experience. Regularly reviewing and adjusting monitoring rules also helps in minimizing false positives and maintaining system effectiveness.