Journal of Economic, Finance Research and Review (JEFRR) · Research article · Open access
Uncovering the Latent Structure of Liquidity Risk Using Machine Learning Clustering Algorithms: Evidence from Vietnamese Commercial Banks
Tran Thi Thuy Huyen, Hoang Thao Nhi, Pham Ngoc Khue, Nguyen Thi Lan Huong, Nguyen Thu Ha, Vu Thi Thu Huong
7 March 2026 · Vol. 2, Issue 3, pp. 148-158
DOI: 10.65150/EP-jefrr/V2E3/2026-02
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What is this article about?
This study explores the latent structure of liquidity risk in the Vietnamese commercial banking system through the application of unsupervised machine learning clustering algorithms. Using panel data collected from the financial statements of 31 Vietnamese commercial banks over the period 2009–2024, the study constructs a set of indicators capturing banks’ liquidity characteristics, profitability, and funding structure.
Article at a glance
- Published
- 7 March 2026
- Volume / issue / pages
- Vol. 2, Issue 3, pp. 148-158
- ISSN
- 3051-3650 (online) · 3051-3642 (print)
- Licence
- CC BY 4.0 — free to read and reuse with attribution
- Peer review
- Double-blind, at least two independent reviewers
- Publisher
- EP Journals Group
Abstract
This study explores the latent structure of liquidity risk in the Vietnamese commercial banking system through the application of unsupervised machine learning clustering algorithms. Using panel data collected from the financial statements of 31 Vietnamese commercial banks over the period 2009–2024, the study constructs a set of indicators capturing banks’ liquidity characteristics, profitability, and funding structure. Representative clustering techniques, including K-means clustering and Hierarchical clustering, are employed to identify groups of banks exhibiting similar levels of liquidity risk. The empirical findings reveal a relatively clear segmentation within the banking system in terms of liquidity stability, associated with differences in operational scale, business performance, and reliance on short-term funding sources. The applied clustering algorithms effectively highlight the underlying structures embedded in the data, thereby reflecting the heterogeneity of liquidity risk across the system. This study contributes to the growing literature by incorporating a machine learning–based approach into liquidity risk analysis and provides empirical evidence to support supervisory practices and prudential risk management in the banking sector.
Keywords: Commercial banks, Clustering, Hierarchical clustering, K-means, Liquidity risk.
Cite this article
Tran Thi Thuy Huyen, Hoang Thao Nhi, Pham Ngoc Khue, Nguyen Thi Lan Huong, Nguyen Thu Ha, & Vu Thi Thu Huong (2026). Uncovering the Latent Structure of Liquidity Risk Using Machine Learning Clustering Algorithms: Evidence from Vietnamese Commercial Banks. Journal of Economic, Finance Research and Review, 2(3), 148-158. https://doi.org/10.65150/EP-jefrr/V2E3/2026-02
@article{Tran2026,
title = {Uncovering the Latent Structure of Liquidity Risk Using Machine Learning Clustering Algorithms: Evidence from Vietnamese Commercial Banks},
author = {Tran Thi Thuy Huyen and Hoang Thao Nhi and Pham Ngoc Khue and Nguyen Thi Lan Huong and Nguyen Thu Ha and Vu Thi Thu Huong},
journal = {Journal of Economic, Finance Research and Review},
year = {2026},
volume = {2},
number = {3},
pages = {148-158},
doi = {10.65150/EP-jefrr/V2E3/2026-02},
url = {https://doi.org/10.65150/EP-jefrr/V2E3/2026-02}
}Questions about this article
Who wrote this article?
Tran Thi Thuy Huyen, Hoang Thao Nhi, Pham Ngoc Khue, Nguyen Thi Lan Huong, Nguyen Thu Ha, Vu Thi Thu Huong.
Where and when was it published?
In Journal of Economic, Finance Research and Review, Volume 2, Issue 3, pages 148-158, published by EP Journals Group on 7 March 2026.
Is this article free to read?
Yes. It is open access under a Creative Commons Attribution 4.0 (CC BY 4.0) licence, so anyone can read, share and reuse it with attribution.
What is the DOI of this article?
10.65150/EP-jefrr/V2E3/2026-02 (https://doi.org/10.65150/EP-jefrr/V2E3/2026-02).
How do I cite this article?
APA: Tran Thi Thuy Huyen, Hoang Thao Nhi, Pham Ngoc Khue, Nguyen Thi Lan Huong, Nguyen Thu Ha, & Vu Thi Thu Huong (2026). Uncovering the Latent Structure of Liquidity Risk Using Machine Learning Clustering Algorithms: Evidence from Vietnamese Commercial Banks. Journal of Economic, Finance Research and Review, 2(3), 148-158. https://doi.org/10.65150/EP-jefrr/V2E3/2026-02
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