Author(s)

He Jingrong ¹, Huang Shan ¹, Cheng Zhaobin ¹, Liang Yu ¹, Liu Yingying ¹

Affiliation(s)

¹ Binjiang College, Nanjing University of Information Science and Technology, Wuxi, Jiangsu, 214000, China

Corresponding Author

He Jingrong

ABSTRACT

With the rapid development of AI technology, the digital transformation in the banking sector has entered a new chapter. This paper thoroughly explores the pivotal role of AI in driving the digital transformation of the banking industry, especially in enhancing operational efficiency and strengthening risk control. The article begins by outlining the background of digital transformation in banking, followed by a detailed introduction to the definition, functions, and implementation methods of AI technology in the banking sector. By analyzing the application of AI in areas such as customer service automation, credit risk assessment, transaction monitoring, and fraud detection, this paper highlights how AI optimizes banking business processes and improves service quality. Furthermore, the article discusses the limitations and challenges encountered in the application of AI, including issues related to technological interpretability and data security. Finally, this paper looks forward to the future development trends of AI in banking, pointing out key influencing factors including technological innovation and the involvement of policymakers. Through in-depth analysis, this paper provides practical guidance and strategic recommendations for the banking industry in the process of AI-driven digital transformation, aiming to promote the continuous development and innovation of the banking sector.

KEYWORDS

AI; Digital Transformation; Banking Industry; Financial Technology

CITE THIS PAPER

He Jingrong, Huang Shan, Cheng Zhaobin, Liang Yu, Liu Yingying, AI-Driven Digital Transformation in Banking: A New Perspective on Operational Efficiency and Risk Management. Information Systems and Economics (2024) Vol. 5: 82-90. DOI: http://dx.doi.org/10.23977/infse.2024.050111.

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