Multi-Chain Asset Tokenization with Automated Compliance Verification

The exponential growth of digital asset tokenization has created unprecedented opportunities for cross-border financial transactions, yet regulatory compliance remains a critical bottle- neck. This research presents a novel multi-chain asset tokenization framework integrated with an AI-driven automated compliance verification system. Our approach addresses the funda- mental challenge of ensuring regulatory adherence across multiple jurisdictions simultaneously while maintaining transaction efficiency and security. The proposed system employs machine learning algorithms to analyze regulatory requirements from various financial authorities and automatically verifies compliance before token deployment. Through extensive experimentation on Ethereum, Binance Smart Chain, and Polygon networks, we demonstrate that our framework achieves 95.7% accuracy in automated compliance verification across major financial regulations including GDPR, SOX, and MiFID II. The system reduces compliance processing time by 87.3% compared to traditional manual verification methods while maintaining a false positive rate below 2.1%. Our contributions include: (1) a unified multi-chain tokenization protocol, (2) an AI-driven compliance verification engine, and (3) a comprehensive evaluation framework for cross-jurisdictional regulatory compliance. The results indicate significant potential for streamlining global asset tokenization while ensuring regulatory adherence, paving the way for broader adoption of blockchain-based financial instruments.