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6.2 Risk Identification, Early Warning, and Control System

RAC emphasizes platform stability and asset security by integrating a smart, AI-powered risk management framework into its core infrastructure. This enables proactive threat detection, real-time alerts, and automated intervention.

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1. Risk Identification System

RAC's risk engine integrates on-chain behavior analysis, user modeling, price volatility tracking, and oracle verification to train its AI risk models. Key focus areas include:

  • Abnormal large transfers (Anti-whale detection)

  • Flash loan exploits

  • Spikes in smart contract call frequency

  • Sudden liquidity withdrawal events (LP Panic Exit)

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2. Real-Time Alert Model

The AI system performs second-level analysis of on-chain data and classifies risk into:

  • Green: Safe and normal behavior

  • Yellow: Mild anomalies flagged for monitoring

  • Red: High-risk behavior; system triggers freeze + manual review

Cross-module integration ensures that, for example, an oracle data anomaly can trigger transaction throttling or contract-level execution restrictions.

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3. Control and Response Mechanisms

  • Multi-signature access control for critical operations (e.g., upgrades, unlocks)

  • DAO fallback protocols such as on-chain asset recovery votes

  • Time-lock execution layers for high-risk transactions, enabling delay and community alerts

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4. User Risk Visibility

Users can monitor their account and asset risk levels in real time via the RAC wallet or dashboard. Personalized risk alerts can be set (e.g., transaction limits, LP withdrawal warnings).

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