This research draws on the verbatim transcript of the complete recording of the Asian Financial Forum opening session held on 26th January 2026 as primary qualitative material. Using close textual interpretation in combination with word frequency and word cloud statistics, sentiment polarity detection, and Term Frequency-Inverse Document Frequency (TF-IDF) with KMeans clustering, the study distills the meeting’s shared understandings, institutional orientations, and strategic signals relevant to firms. The findings indicate that participants framed global uncertainty as a structural and enduring condition and emphasised stabilising long-term expectations through institutional coordination and multilateral cooperation. They highlighted the reduction of fragmentation costs via rule alignment, risk sharing, and enhanced connectivity of cross border financial infrastructure. Hong Kong was positioned as an institutional connector, playing a pivotal interfacing role in the offshore renminbi system, cross market connectivity schemes, and the coordinated development of clearing, settlement, and warehousing networks linked to gold and other commodities. Multilateral development finance was redefined as a builder of confidence and order, providing a stabilising anchor through instrument innovation and co financing when private capital becomes more cautious, while supporting infrastructure investment and the green transition. Sentiment results and negative term patterns suggest that key operational constraints are concentrated in frictions related to clearing, repurchase agreements, taxation, and process costs. The clustering structure further reveals a layered discursive chain spanning policy impetus, cross border institutional linkages, and the operational mechanics of financial markets. On this basis, firms should strengthen governance transparency, verifiable compliance, and quantifiable risk management capabilities, and optimise cross border financing and collaboration through institutionalised channels to enhance resilience and sustainable growth under uncertainty.
References
[1] Bykov, I. A. (2020) Studying political discourse of the President address in Russia with the text mining technique. Journal of Philosophy, Culture and Political Science, 3, 68-75.
[2] Derradj, Y., Toumache, R. (2025) Exploring socioeconomic challenges using latent Dirichlet allocation and text mining: convergence points between World Bank and IMF reports. SocioEconomic Challenges, 9(1), 101-115.
[3] Nam, H., Nam, T. (2021) Exploring strategic directions of pandemic crisis management: a text analysis of World Economic Forum COVID-19 reports. Sustainability, 13(8), 4123.
[4] Hong, X. (2022) Quantitative evaluation of big data development policy: text data analysis based on coword network and policy tools. Mathematical Problems in Engineering, 2022(1), 5141431.
[5] Sun, Z., Zong, Q., Mao, Y., Wu, G. (2024) Exploring the features and trends of industrial product e-commerce in China using text-mining approaches. Information, 15(11), 712.
[6] Seo, Y., Lim, D., Son, W., Kwon, Y., Kim, J., Kim, H. (2020) Deriving mobility service policy issues based on text mining: A case study of Gyeonggi Province in South Korea. Sustainability, 12(24), 10482.
[7] Rice, D. R., Zorn, C. (2021) Corpus-based dictionaries for sentiment analysis of specialized vocabularies. Political Science Research and Methods, 9(1), 20-35.
[8] Mandenaki, K., Sotirakou, C., Mourlas, C., Moschonas, S. A. (2021) Neural embeddings for text analysis: a case study in neoliberal discourse. Journal of Education, Society and Behavioural Science, 34(11), 1-16.
[9] Nelson, L. K. (2020) Computational grounded theory: a methodological framework. Sociological Methods & Research, 49(1), 3-42.
[10] Wo, X., Li, G., Sun, Y., Li, J., Yang, S., Hao, H. (2022) The changing tendency and association analysis of intelligent coal mines in China: a policy text mining study. Sustainability, 14(18), 11650.
[11] Zou, Y., Wang, X., Zhang, Q. (2025) Evolution and quantitative evaluation of China’s green port policies: evidence from text mining and text analysis. Frontiers in Marine Science, 12, 1546755.
[12] Chen, K., Cheng, H., Qin, Q. (2024) Assessing the impact of environmental accounting message disclosure quality on financing costs in high-pollution industries. Journal of Cases on Information Technology (JCIT), 26(1), 1-18.
Share and Cite
Gan, W., Xiao, M., Hashim, F. B., Zhang, J., Mohammed, T. A. (2025) An In-depth Analytical Review of the Opening Session of the Asian Financial Forum and Its Implications for Corporate Development: Based on the Conference Theme of Building a New Order of Financial Cooperation under a Highly Uncertain Global Landscape. Hong Kong Financial Bulletin, 1(5), 34-52. https://doi.org/10.71052/hkfb2025/KBIY2015
