MEXC Launches VVIP System Powered by M Score, Redefining Elite Access Beyond Asset Thresholds

MEXC, one of the world leaders in zero‑fee digital asset trading, announced the launch of the industry-first VVIP system that went live on April 2, 2026. The system redefines VVIP access by moving beyond traditional asset-based eligibility toward a dynamic, multi-dimensional user value-based model. It gives every trader the opportunity to access elite privileges and lays the foundation for a more user-centric ecosystem. At the core of the VVIP system is M-Score, a dynamic metric that reflects user value based on trading activity, account security, and platform engagement. Unlike conventional models that rely primarily on asset holdings or trading volume, M-Score is continuously updated to capture real-time user behavior, offering a more comprehensive and flexible framework for tier qualification. The MEXC VVIP system unlocks a comprehensive suite of premium benefits for users with an M Score of 800 or above. Eligible users can receive exclusive loss coverage to help manage downside during volatile markets, claim APR boosters to earn enhanced interest on their idle assets, and access 24/7 rapid-response support along with expedited handling for large withdrawals through a priority channel. In addition, users can participate in popular platform events with rewards credited instantly, with no manual review required, and receive Elite Experience Cards to share top-tier privileges with their friends. Users at Standard and Premier tiers also receive tier-appropriate benefits, with full details available on the VVIP page. The system is being rolled out in phases, with initial access granted to eligible users. Eligible users can access the VVIP section via the MEXC platform. MEXC will also unveil a major platform event on April 13, with further details to be announced in due course. Access will be reserved for users who achieve a minimum M-Score of 600 (Premier tier and above). MEXC continues to put users first by combining multi-dimensional user value-based evaluation w...