A Study on the Risks and Market Access Regulations for AI- Driven Cross-Border Sharing of Financial Data under the Digital Trade Framework

Abstract

AI technology is reshaping the paradigm of cross-border financial data flows within the digital trade framework, shifting from static transmission to dynamic collaboration and giving rise to threefold risks: data breaches, algorithmic abuse, and sovereignty conflicts. Traditional regulatory logic centered on territorial jurisdiction and post-incident accountability is becoming obsolete. Fragmented international rules lead to regulatory arbitrage and inefficient dispute resolution. A transformative pathway emerges, grounded in three theoretical pillars: sovereignty constraints, collaborative governance, and risk prevention. This approach replaces territorial sovereignty with algorithmic sovereignty, builds a multi-stakeholder collaborative governance network, and implements real-time circuit breaker-style risk prevention. The access system design centers on three core mechanisms: a dynamic data classification list anchored by the AI lifecycle, overcoming limitations of fixed attribute categorization; differentiated entity qualification reviews based on responsibility binding, clarifying the boundaries of rights and responsibilities for financial institutions, technology platforms, and overseas recipients; and a data purpose binding system using technical hardening, achieving “usable but invisible” financial data and automatic compliance. The implementation strategy involves: internally advancing regulatory technology empowerment and collaborative governance platform development; externally adopting a three-step approach—ASEAN pilot programs, Belt and Road expansion, and multilateral rule integration—to embed China's dynamic data classification into the global financial governance framework.