Boost fraud detection accuracy, reduce false positives, and protect merchant portfolios effortlessly with customizable, AI-driven fraud rules.
Enhance control and efficiency by unifying merchant oversight, reducing risk, and ensuring prompt, consistent fraud response across all channels.
Managing thousands of diverse merchants across multiple systems leaves PSPs with blind spots, inconsistent rule application, and delayed reactions to emerging threats.
Excessive chargebacks threaten card-network thresholds, driving up fees, draining reserves, and damaging a PSP’s standing with acquirers and issuers.
Spreadsheet-driven identity and ownership checks slow onboarding, create compliance gaps, and allow bad actors to slip into the payment flow.
Siloed dashboards force analysts to toggle between data sources, delaying fraud decisions and inflating operational costs.
Streamline oversight and reduce risk, empowering PSPs to manage merchants efficiently and securely.
We don’t just promise better fraud control—we deliver tangible improvements that protect your business.
Approve more valid transactions confidently.
Experience double-digit reductions in fraud-related chargebacks
Save time and resources while securing your revenue.
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.
No-code rules engine, flexible dashboards, and tailor-made machine learning models that are designed to adapt seamlessly and scale alongside your business.
Unify fraud detection, compliance, and risk management into one powerful solution, saving valuable time and streamlining your operations.
Reduce false positives, detect and prevent more fraud, and mitigate risk with highly accurate, real-time risk scoring and anomaly detection you can trust.
Leverage advanced analytics, comprehensive reporting, and our Global Anti-Fraud Network to make faster, smarter decisions on the spot.
PSP adaptive fraud rules are dynamic, data-driven algorithms used by Payment Service Providers to detect and prevent fraudulent activities in real-time. These rules leverage machine learning and AI to analyze transaction patterns and adapt to new fraud tactics quickly, ensuring enhanced security while minimizing false positives. They continuously learn from new data, improving their ability to identify suspicious behavior and protect both merchants and customers from fraud.
Adaptive fraud rules differ from traditional methods by using machine learning and AI to continuously update themselves based on new data and patterns. While traditional methods rely on static, predefined rules that may become obsolete, adaptive rules evolve with emerging fraud tactics, providing more accurate and timely detection. This dynamic approach helps reduce false positives and better protect against sophisticated, evolving fraud schemes.
Adaptive fraud rules offer several benefits for PSPs, including enhanced fraud detection accuracy, reduction in false positives, and improved customer experience. By continuously learning from new data, these rules can quickly adapt to emerging fraud tactics, protecting both merchants and customers more effectively. Additionally, they streamline operations by minimizing manual reviews and enabling PSPs to focus on genuine threats, thus optimizing resource allocation and reducing operational costs.
Yes, adaptive fraud rules can be customized for specific industries or businesses. By analyzing transaction patterns unique to a particular sector or company, these rules can be fine-tuned to better detect anomalies and potential fraud. This customization allows PSPs to address industry-specific threats and adapt to the unique risk profiles of different businesses, enhancing the overall effectiveness of fraud prevention measures while maintaining a positive customer experience.
Adaptive fraud rules improve over time by leveraging machine learning algorithms that continuously analyze transaction data and adjust to new fraud patterns. As they process more data, these rules become more accurate in distinguishing between legitimate and fraudulent activities. This ongoing learning process allows them to adapt to emerging threats, reducing false positives and enhancing overall fraud detection capabilities, thus providing more robust protection for merchants and customers.
Machine learning plays a critical role in adaptive fraud rules by enabling them to analyze vast amounts of transaction data and identify patterns indicative of fraud. It allows these rules to learn from historical data and adapt to new fraud tactics in real-time. By continuously updating their models, machine learning helps improve the accuracy and efficiency of fraud detection, ensuring that PSPs can effectively counter evolving threats and minimize both false positives and missed fraud cases.