AI-Driven Governance for Stablecoin Risk and Stability

Abstract

This chapter examines the design, systemic risk behavior, and governance mechanisms of stablecoins within decentralized financial ecosystems. The study categorizes stablecoins into fiat-collateralized, crypto-collateralized, and algorithmic models while analyzing stabilization mechanisms, liquidity dynamics, and regulatory implications. A multi-layer analytical framework named StableGuard-AI is introduced to model temporal risk propagation, governance feedback loops, and cross-market contagion using Bidirectional Long Short-Term Memory networks and Heterogeneous Graph Transformers. The framework integrates uncertainty quantification, explainable artificial intelligence, and governance-aware monitoring to support institutional supervision and decentralized protocol management. Case studies involving the UST collapse, USDC depeg event, DAI market stress episode, and MiCA regulatory developments demonstrate the importance of adaptive risk modeling and transparent governance structures for maintaining financial stability in digital asset ecosystems.