Anti-Money Laundering & Cyber Fraud Database

AIAML’s On-Chain Behavioral Analysis & Risk Detection module is powered by AI algorithms designed to detect illicit behavior patterns across blockchain transactions in real-time. This module analyzes various behaviors, including smurfing, layering, mixer usage, and rapid fund movements, to identify potentially illegal activity. AI-Powered Detection: The AI models evaluate transaction frequency, wallet-to-wallet interactions, and transaction velocity, scoring them based on risk factors and historical laundering trends. The AI identifies outliers and flags unusual activities that may require further human investigation.

Human Analyst Confirmation: While AI can provide an initial risk score, human experts review complex or ambiguous cases to ensure accuracy. For example, a flagged transaction might have a legitimate reason for rapid movement (e.g., a high-frequency trading strategy), which only a human analyst can assess properly based on external factors, such as known customer behavior patterns. AI alerts serve as a starting point, but human validation ensures nuanced decision-making. This dual approach of AI analysis and human review balances efficiency with accuracy, ensuring that high-risk transactions are quickly flagged while minimizing the chances of false alarms.