Fraud.com aiReflex is a fraud detection and prevention platform designed to identify and block fraudulent transactions in real-time across multiple channels. The platform combines machine learning algorithms with rule-based detection to assess risk and trust for account opening, login, and transactional activities. The system includes a transactional orchestration layer that integrates fraud, identity, and cyber solutions through a single API, collecting risk signals and combining them into unified risk scores. The adaptive policy engine provides a drag-and-drop rule editor that works with behavioral models to create and manage detection rules. The AI engine utilizes supervised and unsupervised machine learning models with explainable AI capabilities. It supports PMML (Predictive Model Markup Language) for importing custom models. The platform includes behavioral profiling that creates granular profiles for individuals to detect abnormal behavior patterns. Journey-time orchestration enables automation of operational tasks through a workflow editor that coordinates multiple systems for continuous risk assessment. The case management system provides investigators with a centralized view of fraud cases, incorporating threat-centric grouping that organizes alerts and events based on contextual relationships rather than individual alerts. Additional capabilities include link analysis using graph-based techniques to identify fraud rings, synthetic identities, and account takeover patterns. The platform includes sandbox simulation for testing rules and models against historical data before deployment, along with maker-checker approval controls for rule management.