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Research on Generative AI-Driven Cross-Cultural Financial Product Customization and Marketing Model Innovation

Author(s)

Rong Ye1,2, Ziyuan Zhou3, Muquan Zou1,4,*, Sunyan Hong5, Haixia Shan1

Affiliation(s)

1School of Information Engineering, Kunming University, Kunming, Yunnan, China 2Postdoctoral Research Station, Fudian Bank Financial Research Institute, Kunming, Yunnan, China 3The Hong Kong Polytechnic University, School of Computing and Mathematical Sciences, Hong Kong, China 4Yunnan Key Laboratory of Intelligent Logistics Equipment and Systems, Kunming, Yunnan, China. 5Yunnan Key Laboratory of Cross-border Digital Economy, Kunming, Yunnan, China *Corresponding Author

Abstract

Against the backdrop of an accelerating once-in-a-century global transformation and the profound development of the digital economy, generative artificial intelligence, as a new generation of general-purpose technology, has emerged as a critical pathway to overcoming cultural barriers and demand mismatches in cross-cultural finance. This paper focuses on the application of generative AI in customized cross-cultural financial products and innovative global marketing models. It begins by systematically outlining the key technological components, evolutionary stages, and practical scenarios of generative AI in finance to clarify the inherent value of its technological foundation. Subsequently, drawing upon theories such as cross-cultural communication and financial product design, it constructs a three-dimensional framework for generative AI-driven customization of cross-cultural financial products: in-depth cultural demand identification, automated generation of product elements, and real-time optimization of customization effects. The validity of this framework in multi-ethnic cultural contexts is demonstrated through case studies of Fudian Bank's Jinludai and Jinyidai products. The paper then analyzes how generative AI innovatively empowers cross-cultural financial marketing models across four dimensions: demand insight, content production, channel operations, and effect feedback, revealing its mechanism for reconstructing marketing communication pathways. Finally, it summarizes the advantages and challenges of the cross-cultural financial product customization model. Advantages include precise alignment with cultural needs, strengthened brand identity, and reduced compliance risks, while challenges encompass cultural cognitive biases, technological prejudices, and global coordination difficulties. The paper concludes by envisioning future development directions where products achieve deeper cultural value integration and services evolve toward seamless global connectivity amid technological advancements. This research provides theoretical support for the deep integration of generative artificial intelligence with cross-cultural financial services, contributing to the construction of an open, inclusive, and intelligent global financial ecosystem.

Keywords

Generative Artificial Intelligence; Cross-Cultural Finance; Product Customization; Global Marketing; Model Innovation

References

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