Visualizing Financial Soundness: A Data-Driven Analysis of the Vietnamese Banking Sector

Conventional assessments of financial soundness primarily focus on producing a single risk score or performance ranking. This one-dimensional approach is constrained by two fundamental limitations: it condenses multi-faceted institutional health into a single, often misleading metric, and it creates flawed comparisons between banks with different business models and risk appetites. While useful for risk flagging, this method is insufficient for a structural understanding of the financial landscape. To resolve this tension, we propose an integrated visual analytics framework. Our primary contribution lies in shifting the analytical objective from assigning a score to mapping the ecosystem. By combining Principal Component Analysis and K-Means clustering, our methodology transforms high-dimensional financial data into a multi-dimensional competitive map that makes the magnitude of differences and the diversity of business models explicit. Applied to a panel dataset of 28 Vietnamese commercial banks from 2020 to 2024, our analysis reveals a data-driven taxonomy identifying a ‘Prudential Anchor’ core, a ‘Dynamic Arena’ of competitors, and a singular ‘High-Risk Frontier’ outlier. By providing this holistic map, our study demonstrates a powerful diagnostic tool for regulators and stakeholders to gain a more nuanced, systemic understanding of market structure that transcends the limitations of traditional, one-dimensional assessments.