The paper empirically examines the bank-specific determinants of loan growth in the Vietnamese banking system for the period from 2007 to 2019. We approach the CAMELS framework and employ the dynamic panel regression to determine the effects of each CAMELS factor on bank lending. To ensure the robustness of results, we also use alternative definitions of the variables and different specifications with and without full sets of CAMELS components. With these settings, we display multiple important results. (i) We find that a large capital buffer tends to boost bank lending expansion faster. (ii) High asset quality might positively contribute to high loan growth; in other words, banks subject to high credit risk are discouraged from making loans. (iii) Less efficiently managed banks are more likely to adopt an aggressive lending strategy, highlighting the moral hazard incentives of Vietnamese banks. (iv) More profitable banks with excellent competitive advantages could expand their lending activities to a larger extent. (v) Liquidity is positively related to the loan growth of banks. (vi) Perceived interest rate risk tends to suppress loan growth since interest-rate-sensitive banks might be concerned about the adverse effects of unpredictable adverse changes in interest rates in the future.

The study empirically examines the effects of loan portfolio diversification on bank risk and return in the nascent banking market of Vietnam. Loan portfolio diversification is captured through the Hirschman-Herfindahl index and the Shannon Entropy with sectoral exposures. We access each bank’s financial reports to collect the required data, especially the breakdown of sectoral loan portfolios, thus constituting a unique dataset. To compute bank return, we use the traditional accounting indicators, including return-on-assets, return-on-equity, and net-interest margin. For bank risk, we utilize the loan-loss provisions and non-performing loans relative to gross customer loans. Using a sample of 30 commercial banks over the period from 2008 to 2019 and the system generalized method of moments estimator for the dynamic panel, we indicate the downsides of portfolio diversification. Concretely, we observe that all diversification measures exhibit significantly negative signs in all regressions across different bank return proxies. At the same time, the estimates display the significant and positive impact of diversification on the non-performing loan ratio. Hence, sectoral loan portfolio diversification significantly hampers bank performance in both aspects of lower return and higher credit risk. The results are robust across a rich set of bank performance and portfolio diversification measures.