Payegis Inc. （通付盾）

Fraud is an explosive problem in online transactions. Because fraudsters are driven and highly motivated to constantly innovate, we need tools to proactively and faster innovate new ways and means to fight current and emerging fraud in order to achieve profitability in online business. Existing fraud solutions cannot quickly adapt to new emerging fraud, they are usually post event analysis, lack of impact analysis and experimental platform, and disconnected from offer sentiment. The general basis for anomaly detection and fraud detection is pattern recognition. An effective online fraud detection system should be able to discover both known and new attacks as early as possible. The detection process should be self-adjustable to allow the system to deal with the constantly changing nature of online attacks. We provide consumer facing business with fraud detection, forensics, and ongoing risk monitoring using strong analytic and rich, predictive models of individual user behavior. We have real-time adaptive risk management framework, which tracks and scores interested attributes declared on the fly, a.k.a., dynamical reputation management. Combining both predictive model and rule techniques, we provide experimental platform to simulate and optimize profitability on historical transactions and predictive model (including offer sentiments). We help achieve accuracy and speed by performing impact analysis and rule simplification before policy enforcement. We beat fraudsters by automatically detecting new and evolving fraud threats–delivering actionable alerts and rapid investigation capabilities. We help achieve profitability by encouraging transactions and minimizing fraud risk based on predefined risk reach ratio.