Blockchain and Machine Learning for Automated Compliance in Regulatory Technology

Blockchain and Machine Learning integration has changed the area of Regulatory Technology (RegTech), offering automated compliance solutions for difficult regulatory issues. By combining the benefits of blockchain technology with machine learning algorithms, this article introduces a unique Compliance Assurance Framework utilizing BlockchainEnhanced Machine Learning (CAF-BEML) to improve the effectiveness and trustworthiness of compliance procedures. The Blockchain-Enhanced Compliance Data Verification Algorithm (BCDVA), the Predictive Regulatory Risk Assessment Algorithm (PRRA), and the Secure Compliance Audit Trail Algorithm (SCATA) are the three central algorithms in the proposed framework, and they work together to guarantee data authenticity, forecast potential threats, and generate clear audit trails, all of which contribute to a robust regulatory ecosystem. The suggested method's effectiveness and superiority over current conventional approaches are proved, and its potential to change compliance management in numerous industries is emphasized via this in-depth study and comparison.