Are These Growing Fraud Challenges Putting Your Bank at Risk?
Protect your bank from evolving fraud risks with proactive solutions that enhance security, reduce friction, and streamline operations.
Increasingly Sophisticated Fraud Schemes
Banks face account takeovers, synthetic IDs, mule accounts, and cross-channel attacks that evolve faster than rule-based tools can adapt, exposing institutions to mounting financial and reputational risk.
High False Positives and Customer Friction
Legacy filters flag too many legitimate transactions, forcing manual reviews, delaying funds availability, and frustrating valued clients who expect seamless, always-on digital banking experiences.
Siloed Systems, Fragmented Data
Core banking, card, ACH, and wire platforms rarely share context, preventing teams from seeing a unified customer risk picture and slowing coordinated fraud response.
Slow or Inconsistent Decisioning
Batch processes and disconnected workflows delay detection, allow losses to grow, and create uneven policy enforcement that troubles auditors and regulators.
Revolutionize Fraud Detection with Intelligent Solutions
Protect your bank with Fraudnet's advanced solutions, ensuring seamless security and satisfied customers.
AI-Native Fraud Models
Learns patterns; flags takeover and identity fraud in milliseconds.
Real-Time Transaction Monitoring
Screens every payment in milliseconds, blocking suspicious activity.
Entity-Centric Risk Profiling
Unifies identity, device, and behavior into one risk score.
Intelligent Risk Decisioning Engine
Combines ML and rules to auto-approve, challenge, or decline.
Real-Time Cross-Channel Protection
Monitor digital, card, ACH, wire, and branch transactions in milliseconds to prevent threats before they impact your accounts. Ensure seamless customer service while maintaining robust protection against evolving fraud tactics.
Lower False Positives, Happier Customers
With FraudNet's adaptive AI-native scoring, you experience fewer declined legitimate transactions, reducing operational workload and enhancing client satisfaction. Enjoy seamless digital banking that keeps your customers happy and your processes efficient.
Accelerated Investigations on One Dashboard
Easily streamline investigations with a unified dashboard featuring case histories, automated workflows, and audit-ready trails. Reduce review times, cut costs, and maintain regulatory confidence, empowering your team to act swiftly and effectively.
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
Speak with our Solutions Expert Today
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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. These systems utilize advanced algorithms and machine learning to detect anomalies and patterns indicative of fraudulent activity. By analyzing transaction data and user behavior, the software can quickly flag suspicious activities for further investigation.
How does machine learning enhance fraud detection?
Machine learning enhances fraud detection by continuously learning from new data and adapting to emerging fraud patterns. It employs algorithms that can process large volumes of transactions, identifying subtle anomalies and correlations that might be missed by traditional rule-based systems. This dynamic approach allows for more accurate prediction of fraudulent activities and minimizes false positives, improving overall detection efficiency.
What is the role of real-time monitoring in fraud detection?
Real-time monitoring is crucial in fraud detection as it allows financial institutions to detect and respond to fraudulent activities almost instantly. By analyzing transactions as they occur, the software can quickly flag suspicious activities, preventing potential losses and protecting customer accounts. This immediate response capability is essential in minimizing the impact of fraud and enhancing customer trust.
How do fraud detection systems handle false positives?
Fraud detection systems handle false positives by employing sophisticated algorithms and machine learning models that refine and improve accuracy over time. They prioritize anomalies with the highest probability of fraud, reducing unnecessary alerts. Additionally, systems often include mechanisms for human review and feedback, allowing analysts to adjust parameters and improve the system's precision through continuous learning.
What role does data analytics play in fraud detection?
Data analytics plays a pivotal role in fraud detection by enabling the analysis of vast amounts of transaction data to identify unusual patterns and trends. By leveraging statistical methods and machine learning, analytics helps detect anomalies and predict potential fraud scenarios. This data-driven approach enhances the ability to prevent fraud by providing actionable insights and supporting decision-making processes.
Can fraud detection software integrate with existing banking systems?
Yes, fraud detection software is designed to integrate seamlessly with existing banking systems. This integration allows for the efficient flow of data between different platforms, ensuring comprehensive monitoring and analysis. By working alongside current systems, the software can enhance fraud detection capabilities without disrupting existing operations, making it a flexible and scalable solution for financial institutions.