Sovereign Algorithms, Borderless Finance: Navigating Legal Pathways for EU-China Fintech AI Integration Amidst Data Localization Regimes

Abstract

The convergence of financial technology (fintech) and artificial intelligence (AI) promises unprecedented efficiency in credit scoring, fraud detection, and algorithmic trading. However, the deployment of these technologies across the European Union (EU) and the People's Republic of China (PRC) is increasingly obstructed by divergent data sovereignty regimes. This article examines the legal pathways available for EU fintechs utilizing China-trained AI models, and vice versa, within the context of conflicting data localization rules. By analyzing the General Data Protection Regulation (GDPR), the EU AI Act, China's Personal Information Protection Law (PIPL), and the Data Security Law (DSL), this paper identifies the jurisdictional friction points regarding cross-border data transfers. It argues that while traditional transfer mechanisms (such as adequacy decisions) are politically unviable, technical-legal hybrids - specifically federated learning, model localization, and synthetic data generation - offer the only viable compliance architecture. The article concludes with recommendations for regulatory sandboxes and mutual recognition of technical standards to mitigate the risk of technological decoupling in the financial sector.