Are You Struggling with These Merchant Risk Challenges?
Elevate your risk management strategy by addressing merchant challenges head-on, reducing penalties, operational costs, and revenue loss.
Unmanaged Merchant Risk
Periodic reviews leave gaps where bad actors can spike refunds, exceed fraud ratios, and expose the processor to card-network penalties.
Manual Monitoring Bottlenecks
Analysts juggle Excel sheets and siloed gateways, slowing issue detection, inflating labor costs, and delaying merchant remediation.
Chargebacks & Threshold Violations
Late identification of rising disputes triggers costly fines, holds, and potential loss of acquiring bank relationships.
High False-Positive Rates
Rigid rule sets often decline legitimate volume, hurting merchant revenue and driving unnecessary support escalations.
FraudNet Solutions: Proactively Safeguard Merchants and Profits
Enhance security, reduce costs, and protect relationships with smart risk management tailored for payment processors.
Policy Monitoring Engine
Live merchant policy monitoring blocks breaches before networks issue fines.
Anomaly Detection Models
ML anomaly detection flags hidden fraud patterns missed by static rules.
Merchant-Level Thresholds
Adaptive thresholds tailor risk scores to each merchant, lowering false positives.
Real-Time Alerts
Instant alerts route critical events to your team via API, email, or Slack.
AI-Native, Millisecond Scoring
FraudNet's AI-driven, millisecond scoring evaluates each transaction and refund instantly, leveraging global signals to intercept fraud before authorization. This ensures legitimate volume flows smoothly, bolstering merchant satisfaction and securing processor margins while maintaining robust fraud prevention.
Unified Risk & Case Console
Our unified risk & case console streamlines your operations by integrating data from PSPs, gateways, and CRMs. It auto-prioritizes investigations, slashing analyst review time by up to 70%, enhancing efficiency, and empowering your team to act faster against fraud.
Precision Without Friction
Our dynamic models slash false positives by up to 30%, ensuring smoother transactions and happier merchants. This efficiency not only reduces your operational costs but also safeguards your processor margins, delivering a seamless experience that boosts 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 AI risk scoring in payment processing?
AI risk scoring in payment processing involves using artificial intelligence algorithms to evaluate the risk level of transactions. This system analyzes various data points, such as transaction history, user behavior, device information, and location, to assign a risk score. A higher score indicates a higher risk of fraud or suspicious activity. This helps payment processors and financial institutions make informed decisions about approving, declining, or flagging transactions for further review.
How does AI improve risk assessment in payment processing?
AI enhances risk assessment by leveraging machine learning models that can recognize complex patterns and anomalies in transaction data more effectively than traditional rule-based systems. AI systems continuously learn from new data, allowing them to adapt to emerging fraud tactics and reduce false positives. This dynamic approach helps payment processors detect fraudulent activities in real-time, improve accuracy in risk scoring, and ensure a smoother transaction flow for legitimate customers.
What data is used by AI for risk scoring in payment processing?
AI for risk scoring utilizes a variety of data, including transaction details (amount, currency, time), user information (account history, demographic data), device and network data (IP addresses, device IDs), and behavioral patterns (purchase frequency, typical transaction amounts). Additionally, external data sources such as blacklists, geolocation, and even social media activity can be integrated. This comprehensive data analysis helps in creating a more accurate and context-aware risk profile for each transaction.
What are the benefits of using AI for risk scoring in payment processing?
The benefits of using AI for risk scoring include improved detection of fraudulent activities, reduced false positives, faster transaction processing, and enhanced customer experience. AI-driven systems can quickly identify unusual patterns that may indicate fraud, leading to timely interventions. Moreover, by minimizing false positives, customers face fewer disruptions, which increases satisfaction and trust. Additionally, AI systems can scale to handle large volumes of transactions, making them ideal for growing businesses.
How does AI risk scoring handle emerging fraud tactics?
AI risk scoring handles emerging fraud tactics by continuously learning from new data and adapting its algorithms to identify novel patterns and anomalies. Machine learning models are designed to evolve as they process more transactions, allowing them to detect previously unseen fraud techniques. By integrating feedback loops and updating models regularly, AI systems can stay ahead of fraudsters who constantly change their methods to bypass traditional security measures.
What are the challenges of implementing AI risk scoring in payment processing?
Implementing AI risk scoring can present challenges such as data privacy concerns, model bias, integration with existing systems, and the need for ongoing model training and validation. Ensuring data security and compliance with regulations like GDPR is crucial. Additionally, AI models must be transparent and fair, avoiding biases that could unfairly affect certain user groups. Successfully integrating AI solutions requires technical expertise and collaboration across departments to align with business objectives.