거래 사기를 탐지하는 데 사용하는 SQL 패턴

SQL-based fraud detection patterns offer practical, scalable alternatives to machine learning for catching transaction anomalies across payments, healthcare, and e-commerce domains. By implementing velocity analysis, impossible travel detection, amount anomalies, and merchant pattern monitoring, organizations can shift detection cycles from weeks to hours while reducing false positives through whitelist management. This approach is particularly valuable because it provides immediately deployable rules without requiring complex ML infrastructure or extensive historical baseline data.