Are These Hidden Risks Undermining Your Merchant Portfolio?
Identify and mitigate hidden risks with real-time insights, safeguarding your portfolio and strengthening acquirer–merchant relationships.
High Chargeback Exposure
Excessive refund and chargeback ratios trigger costly scheme fines and reserve hikes, directly eroding your interchange margins and damaging acquirer–card-network relationships.
Onboarding Risk of High-Risk Merchants
Without real-time KYB, acquirers may board shell companies, illicit storefronts, or sanctioned entities, leading to compliance violations, reputational damage, and sudden portfolio losses.
Fraudulent Transactions Across Portfolios
CNP fraud, refund abuse, and friendly fraud move fast across merchant networks, yet legacy batch tools delay detection, letting bad actors drain authorization volume unchecked.
Limited Merchant Behavior Visibility
Siloed data and manual reviews obscure rising decline rates, refund spikes, or device anomalies, preventing early intervention and exposing the acquirer to cascading risk.
FraudNet Solutions: Instantly Combat Fraud and Minimize Risks
Fraudnet empowers acquirers to swiftly detect and mitigate risks, safeguarding portfolio integrity and profitability.
Real-Time Policy Monitoring
Live alerts on chargebacks, refunds, or volumes stop breaches instantly.
Enhanced KYB Risk Scoring
KYB blends identity, device, behavior to flag risky merchants pre-board.
Instant Transaction Scoring
ML scores every CP/CNP authorization in ms, blocking fraud in flow.
Unified Merchant Dashboard
Single view surfaces risk, trends, and policy breaches at a glance.
AI-Native, Millisecond Decisions
FraudNet evaluates each authorization instantly, adapting to new fraud patterns to block threats before they impact settlements. This proactive approach ensures you maintain genuine transactions, protect your bottom line, and strengthen trust within your payment network.
360° Merchant Intelligence
Elevate your risk management strategy with our centralized dashboard that integrates KYB, transaction, and behavioral data. Empower your underwriters and risk teams with instant insights into thresholds, trends, and anomalies, ensuring proactive measures and safeguarding your portfolio against unforeseen risks.
Configurable Policy Engine
Customize your chargeback, volume, and refund policies to match your risk tolerance effortlessly. Automate alerts and minimize manual reviews to slash losses and protect your growth trajectory, ensuring your portfolio remains robust and resilient in an ever-evolving market landscape.
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, among others. By analyzing transaction patterns and using machine learning algorithms, these systems can detect anomalies that indicate potential fraudulent activity, helping acquirers mitigate risks and protect their merchants from financial loss.
How does real-time fraud detection work for acquirers?
Real-time fraud detection for acquirers operates by continuously monitoring transactions as they occur. It uses advanced algorithms and machine learning models to analyze transaction data, looking for patterns or anomalies that could indicate fraud. When suspicious activity is detected, the system can flag the transaction for review or automatically block it, allowing acquirers to respond quickly and prevent potential losses.
What are the benefits of real-time fraud detection for acquirers?
The benefits of real-time fraud detection for acquirers include improved security and reduced financial losses due to fraud. By identifying and stopping fraudulent transactions instantly, acquirers can protect their merchants and cardholders. Additionally, real-time detection helps maintain customer trust, reduces chargeback rates, and enhances operational efficiency by minimizing the need for manual reviews of fraudulent activities.
What are common challenges faced in implementing real-time fraud detection?
Common challenges in implementing real-time fraud detection include managing false positives, ensuring system scalability, and maintaining high processing speeds without compromising accuracy. Balancing the need for stringent security measures with a seamless customer experience is also crucial. Acquirers need to continuously update their systems to adapt to evolving fraud tactics and ensure integration with existing payment processing infrastructure.
How does machine learning enhance fraud detection capabilities?
Machine learning enhances fraud detection by enabling systems to learn from historical transaction data and improve their accuracy over time. These models can identify complex patterns and adapt to new fraud tactics that traditional rule-based systems might miss. By continuously updating their algorithms based on new data, machine learning models help acquirers detect fraud more effectively and reduce false positives, ensuring a balance between security and user experience.
What role do data analytics play in acquirer fraud detection?
Data analytics play a crucial role in acquirer fraud detection by providing insights into transaction behaviors and identifying patterns indicative of fraud. Analyzing large volumes of transaction data helps in developing predictive models that can forecast and prevent potential fraud. By leveraging data analytics, acquirers can make informed decisions, enhance their fraud detection strategies, and improve the overall security of the payment ecosystem.