The Impacts of Generative Artificial Intelligence on Financial Research：Opportunities，Challenges，and Prospects

The rapid development of Generative Artificial Intelligence （GenAI） has exerted a broad and far-reaching influence on disciplines that rely heavily on data as a core research input. Against this backdrop，this paper investigates the transformation of financial research under the impact of GenAI from the dual perspectives of paradigm transformation and theoretical extension. Using a bibliometric approach that integrates semantic clustering with large language models，this study provides a comprehensive overview of how GenAI has spread within financial research. From the standpoint of research paradigms，this study analyses the roles of GenAI in data synthesis，hypothesis generation and simulation-based validation，and identifies both the new research opportunities it creates and the methodological risks it entails，including bias amplification，logical hallucinations and opacity. From the perspective of theoretical extension，the paper discusses how GenAI supports the expansion and deepening of core frameworks related to information asymmetry，behavioral finance and corporate governance. Finally，this study highlights four key directions that warrant further investigation：enhancing methodological reliability，strengthening causal identification，examining behavioral patterns under human-AI collaboration and improving the conceptualization of AI-related risks in finance.