Determinants of bank profitability in Vietnam: Integrating digital transformation, ESG, and market structure

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Type of the article: Research Article

Abstract
Bank profitability remains a central concern in emerging economies, particularly Vietnam, where commercial banks face traditional financial pressures and new strategic challenges. This study analyzes 20 Vietnamese banks during the period 2015–2024, integrating traditional bank-level indicators, macroeconomic variables, and innovation drivers (digital transformation and ESG). Profitability is measured by Return on Assets (ROA) and Return on Equity (ROE) from audited financial statements. We use a dynamic panel framework with unit root and cointegration tests, and estimate the model using the Arellano-Bond GMM method; the model selection and validity are supported by F, Hausman, and Breusch-Pagan tests. Robustness is assessed through pooled OLS, fixed effects, random effects, and feasible GLS.
The results show sustainable profitability: lagged ROE ≈ 0.42 (p < 0.001). Non-interest income (NII ≈ 0.21, p < 0.001), liquidity (LIQ ≈ 0.036, p = 0.002), and real GDP growth (GDP ≈ 0.020, p = 0.005) positively impact ROE. Innovation drivers – digital transformation (≈ 0.041, p = 0.004) and ESG efficiency (≈ 0.057, p = 0.011) – also contribute to improved profitability. Conversely, higher capital adequacy ratios (≈ −0.040, p = 0.004), deposits (≈ −0.016, p = 0.008), and operating expenses (≈ −0.021, p = 0.001) reduced ROE; inflation and credit risk indicators were negligible. Integrating traditional and strategic factors provides a more comprehensive view of bank performance and suggests policymakers should balance regulatory stability, innovation, and sustainability to support bank profitability.

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    • Table 1. Descriptive statistics of Vietnamese commercial banks (2015–2024)
    • Table 2. Diagnostic test results for model validation
    • Table 3. Regression results (FEM vs. 2SLS)
    • Table 4. Dynamic panel GMM estimation of profitability persistence and innovation effects
    • Table 5. Subgroup regression results by bank size, ownership type, and geographic location
    • Table A1. List of 20 Vietnamese commercial banks included in the data panel (2015–2024)
    • Conceptualization
      Tuan Van Ngo
    • Data curation
      Tuan Van Ngo
    • Formal Analysis
      Tuan Van Ngo
    • Investigation
      Tuan Van Ngo
    • Methodology
      Tuan Van Ngo
    • Project administration
      Tuan Van Ngo
    • Resources
      Tuan Van Ngo
    • Software
      Tuan Van Ngo
    • Validation
      Tuan Van Ngo
    • Visualization
      Tuan Van Ngo
    • Writing – original draft
      Tuan Van Ngo
    • Writing – review & editing
      Tuan Van Ngo