AIGC Technology in the Fintech Sector: An Analysis of Theme Evolution Based on the BERTopic Model

Artificial Intelligence Generated Content (AIGC) is reshaping the fintech sector by enabling automation, enhancing efficiency, and transforming data-driven decision-making. However, there is still a lack of systematic understanding of how AIGC-related topics have evolved over time across different languages and types of literature. To address this gap, this study applies the BERTopic model to analyze a multi-source corpus comprising 1,168 documents, including journal articles and patents in both Chinese and English. The analysis reveals distinct thematic patterns: English-language literature shows mature and diverse topic development, while Chinese-language sources highlight emerging areas of innovation. In contrast, patent data reflects decreasing relevance over time, indicating faster technological turnover and the need for practical alignment. This cross-linguistic, multi-type analysis provides a comprehensive view of AIGC’s knowledge evolution in fintech and offers insights into future research directions and innovation opportunities.