List of tables and figures Tables: Table 1: Overall studies Table 2: Model choosing process Table 3: Description of the variables used in the regression model Table 4: Summary of data
Introduction
Liquidity was a crucial factor in the global financial crisis, as noted by Bordeleau and Graham (2010) The uncertainty during the crisis led to the evaporation of funding sources, resulting in a cash shortage for commercial banks to meet their debt obligations This situation caused some banks to fail and others to merge, leading to a contagion effect that spread to numerous countries Despite the crisis being over for over a decade, liquidity issues remain relevant today Additionally, Marozva (2015) highlights ongoing debates about whether banks fully understood the implications of liquidity management following the crisis.
The Covid-19 pandemic has significantly altered the banking business model, with experts like Vives et al (2020) noting that low interest rates are likely to persist, initially benefiting banks through enhanced liquidity and loan creation However, this short-term advantage may lead to an increase in non-performing loans, potentially jeopardizing banks' solvency, reminiscent of the 2008 financial crisis KPMG (2022) highlights that global supply chain disruptions have driven up material costs, contributing to rising inflation Mena (2023) indicates that the inflationary battle began in March 2022, following the Federal Reserve's first interest rate hike, which reached 5.12% by July 2023.
The collapse of Silicon Valley Bank (SVB), along with Signature Bank and Silvergate, was primarily driven by high interest rates (Polychroniou, 2023) At the time, SVB held approximately 55% of its assets in low-risk fixed-income securities, such as U.S government bonds, with plans to hold them to maturity However, depositor concerns led to a significant withdrawal of funds To address liquidity shortfalls, SVB sold $21 billion of its securities at a $1.8 billion loss and attempted to raise over $2 billion in new capital This decision eroded depositor confidence, triggering a second wave of withdrawals that ultimately resulted in SVB's collapse (Tennekoon, 2023).
Many banks in Vietnam are currently grappling with a high ratio of non-performing loans, largely due to the unchecked issuance of corporate bonds, which were initially backed by commercial banks and gained significant customer trust However, rising inflation and increased interest rates have caused these corporations to struggle in meeting their debt obligations, resulting in a shift of debts from performing to non-performing categories Consequently, banks are now burdened with a substantial amount of illiquid assets, primarily in real estate, raising concerns about their liquidity and overall performance.
For this reason, this research is conducted to extend the understanding of the correlation between liquidity and banks’ performance in Viet Nam by two research questions:
1 What is the impact of liquidity on banks' performance in Viet Nam?
To improve and control liquidity issues, the State Bank of Vietnam and commercial banks should implement a series of strategic measures These include enhancing liquidity management frameworks, optimizing asset-liability matching, and diversifying funding sources to reduce reliance on short-term borrowing Additionally, fostering stronger communication and collaboration between banks and regulatory authorities can improve transparency and responsiveness to market changes Implementing advanced technology and data analytics can further aid in monitoring liquidity positions in real-time, ensuring proactive decision-making Lastly, promoting a robust risk management culture within banks will contribute to overall financial stability and performance in the banking system.
This paper is structured into six key sections Following the introduction, the literature review will define liquidity and examine its impact on bank performance, alongside a discussion of relevant previous research to identify suitable variables for the Vietnamese banking context The methodology section will detail the methods, data collection processes, variables, and models utilized in this study Empirical results will be presented, interpreted, and discussed, focusing on the relationship between liquidity and bank performance Policy recommendations will be provided to enhance future outcomes, and the conclusion will summarize the research findings while addressing its limitations.
Literature review
Theory of liquidity
John Maynard Keynes introduced the concept of 'liquidity' in his 1936 work, The General Theory of Employment, Interest and Money, where he elaborated on the 'Liquidity Preference Theory.' This theory highlights the relationship between interest rates and the amount of money individuals prefer to hold, indicating that investors demand higher interest rates over time due to increased risk, with cash being the most liquid asset Additionally, Keynes identified three key motives for the public's demand for liquid cash: the transaction motive, the precautionary motive, and the speculative motive.
In the past, the underdeveloped banking system led to a high public demand for cash for transactions Today, with a well-developed banking infrastructure facilitating billions of daily transactions, the demand for cash primarily stems from precautionary and speculative motives, as exemplified by the Silicon Valley Bank (SVB) situation Damage to a financial institution's reputation can significantly impact liquidity management, potentially triggering bank runs or crises A historical example is Lehman Brothers, which faced a loss of market confidence due to issues like high leverage, poor risk management, and weak oversight, leading to a withdrawal of services and credit lines from other banks and resulting in intermittent liquidity problems To assess a firm's liquidity, metrics such as the current ratio or cash ratio are commonly used.
10 etc are usually being used (Rehayem, 2019) However, for commercial bank, the it is very important to consider money deposit in both short-term and long-term.
Definition of bank performance
Profitability, as defined by Bagh et al (2016), reflects a firm's financial performance, particularly in commercial banking, by assessing the monetary outcomes of its strategies and activities In both global and Vietnamese contexts, return on assets (ROA) and return on equity (ROE) are key ratios used to evaluate bank performance Gallo (2016) explains that ROA is derived by dividing net income by total assets, while ROE is calculated by dividing net income by total equity ROE indicates the return on shareholders' investments, whereas ROA measures the effectiveness of generating income from bank assets Consequently, when comparing banks of similar size, those with higher ROA and ROE demonstrate superior business and investment performance, as noted by the U.S Securities and Exchange Commission.
In 2007, Bear Stearns experienced a 3.2% decline in profit before tax compared to 2006, with a return on average common equity plummeting to just 1.8%, down from 19.1% in fiscal 2006 This financial downturn led to Bear Stearns being acquired by JPMorgan in early 2008 (Reuter, 2008).
Impact of liquidity on bank performance
The National Credit Union Administration utilizes the CAMEL rating system to assess the financial performance of banks and financial institutions CAMEL represents five key components: Capital, Assets, Management, Earnings, and Liquidity Effective management of liquidity is crucial for maintaining the overall financial health of these institutions.
11 performance will be expected to be better However, there are some claims that banks have to sacrifice their liquidity to achieve a better performance
Nishanthini and Meerajancy (2015) investigated the correlation between liquidity ratios—Current ratio and Quick ratio—and financial performance indicators such as ROA, ROE, and Net Profit margin in Sri Lanka's State and Private banks from 2008 to 2012 Their findings revealed a negative relationship between liquidity and bank performance, indicating that banks holding excessive liquid assets to manage liquidity issues tend to experience decreased profitability, as these assets primarily consist of cash and cash equivalents that yield minimal returns Additionally, the study highlighted that the chosen time frame followed the global financial crisis, suggesting that banks may have adopted a more cautious approach compared to the pre-crisis period.
Adeyanju (2011) conducted research utilizing both primary and secondary data, concluding that both illiquidity and excess liquidity negatively impact the profitability of banks in Nigeria, categorizing them as 'financial diseases.'
A study conducted in 2018 analyzed 30 commercial banks in Bangladesh over a five-year period from 2011 to 2016, focusing on profitability indicators such as Return on Assets (ROA), Return on Equity (ROE), and Net Profit (NP) The research employed a Fixed Effect Regression model to explore the correlation between these profitability variables and loan ratios alongside interbank ratios The findings suggested that, after ensuring minimum liquidity, banks should prioritize utilizing customer deposits and borrowings for high-quality loans to enhance shareholder earnings and improve ROE.
A study conducted by Paul et al (2020) analyzed forty commercial banks in Bangladesh from 2009 to 2018, focusing on Return on Equity (ROE) as the sole dependent variable The research examined five different liquidity metrics, including the Loan to Deposit Ratio (LDR), Deposit to Assets Ratio (DAR), and Cash and Cash Equivalents to Deposit.
The study found a correlation between Loan to Deposit Ratio (LDR), Debt to Asset Ratio (DAR), and Cash Deposit Ratio (CDR) with Return on Equity (ROE), while Liquid Assets Ratio (LAR) and Current Ratio (CR) were not significant The authors recommended that banks in Bangladesh should maintain a balance between liquidity and profitability.
Malik et al., (2016) chose twenty-two private sector banks in Pakistan from
From 2009 to 2013, Ordinary Least Squares (OLS) analysis revealed a significant relationship between liquidity and Return on Assets (ROA), while no significant correlation was found for Return on Equity (ROE) and Return on Investment (ROI) The findings suggest the need for restructuring liquidity management strategies to boost returns on shareholders' equity and optimize asset utilization.
A study by Lukorito et al (2014) highlights that the financial sector in Kenya, similar to Vietnam, is primarily dominated by commercial banks Analyzing 43 commercial banks from 2009 to 2013, the research found a strong positive correlation between liquidity and return on assets (ROA), indicating that a 1% increase in liquidity results in an 86.3% rise in profitability To maximize profits, banks are encouraged to invest significantly in assets while ensuring adequate liquidity through short-term marketable securities Furthermore, the study recommends actively pursuing viable investment opportunities and aligning them with customer deposits to enhance profitability.
Lartey et al (2013) analyzed seven banks listed on the Ghana Stock Exchange to explore the relationship between liquidity and profitability using time series analysis from 2005 to 2010 Their findings revealed a decline in both liquidity and profitability during this period, with a very weak positive correlation between the two variables They cautioned that excessive liquid assets or low-return assets could lead to opportunity costs that overshadow the benefits of increased liquidity Similarly, Charmler et al (2018) examined the impact of liquidity on the performance of 21 commercial banks in Ghana over a decade, from 2007 to 2016 Their study employed liquidity ratios, finding a weak effect of liquidity assets to total assets on Return on Assets (ROA) and no significant impact on Return on Equity (ROE) when analyzing liquidity assets to total loans The latter ratio, which acts as a quick ratio, assesses the short-term solvency and liquidity of banks.
The research of Ibrahim (2017) chose 5 commercial banks in Iraq from 2005 to
In a 2013 study using an OLS model, the independent variables of Loan Deposit Ratio, Deposit Asset Ratio, and Cash Deposit Ratio were analyzed alongside Return on Assets (ROA) The findings indicated positive relationships between all three variables and ROA, leading to recommendations for increasing customer deposits and maintaining higher cash reserves However, the research faced significant limitations, including a small sample size from over thirty banks in Iraq and the lack of published annual reports from many institutions.
14 reports, particularly income statements and balance sheets in their site and in the Iraqi Stock Exchange (ISX) For these reasons, the result of this research could be very biased
Pasiouras and Kosmidou (2007) analyzed factors affecting the profitability of domestic and foreign banks within the European Union, utilizing a sample of 584 commercial banks from 15 EU countries between 1995 and 2001 Their findings revealed a mixed impact of liquidity on profitability; while an increase in liquid assets negatively affected domestic banks, it positively influenced foreign banks Additionally, both inflation and GDP growth exhibited a similar trend, showing a positive correlation for domestic banks and a negative one for foreign banks The authors concluded that domestic banks have greater opportunities to adjust interest rates effectively, enabling them to achieve higher profits.
In their study of ten commercial banks in Turkey from 2002 to 2010, Alper and Anbar (2011) found that internal and external factors influenced bank performance Notably, liquidity, inflation, and GDP growth rate showed no correlation with bank performance However, the real interest rate demonstrated a positive relationship with Return on Assets (ROA) and Return on Equity (ROE) The authors recommended that banks should prioritize increasing their size and non-interest income to enhance profitability.
Research gap
The relationship between liquidity and bank performance is complex, exhibiting both positive and negative aspects Previous research primarily utilized panel data and various methodologies, such as OLS, Fixed Effect Regression, and Random Effect Regression, leading to differing outcomes It's important to note that different countries exhibit unique characteristics, and most studies have focused on the correlation between liquidity and bank performance While many studies indicate a negative relationship, they do not overlook the significance of effective liquidity management Consensus among authors suggests that liquidity should be maintained at a minimum level, with excess funds invested in highly liquid assets like treasury bonds or securities to optimize profitability.
This paper analyzes the relationship between liquidity and bank performance in Vietnam, positing that increased liquidity positively influences bank performance It addresses a research gap by focusing on different time frames and country-specific variables tailored to the Vietnamese context Recent global challenges, including the U.S.-China trade war (2018-2019), the onset of Covid-19 leading to widespread lockdowns and supply chain disruptions, and the Russia-Ukraine conflict in 2022, have further emphasized the importance of understanding liquidity dynamics in this environment.
In 2023, significant events among major global nations have led to shifts in policies and financial factors, such as inflation and interest rates, impacting smaller countries like Vietnam These changes highlight the need for adaptation to an increasingly unstable economic landscape.
This paper addresses a significant research gap by examining the unstable period from 2012 to 2022, as data from certain banks prior to 2012 is unavailable and not reported quarterly.
Describe statistics and inferential statistics
(Collection of both primary and secondary data)
Fixed Effect Regression Paul et al., (2020) Bangladesh
Ordinary Least Squares (OLS) Lukorito et al.,
Source: Author compilation Table 1: Overall of studies
Data and Methodology
Data sources and research methods
The research utilizes a combination of cross-sectional and time series data (panel data) spanning from 2012 to 2022, focusing on internal bank variables such as ROA and ROE, with data sourced from Vietstock and verified against annual audited consolidated financial reports A total of 30 banks were selected based on data from the State Bank of Vietnam (SBV), although incomplete data over several years necessitated the use of annual rather than quarterly data, with the list of selected banks provided in the Appendix Additionally, independent variables like 'Inflation' and 'GDP' were obtained from World Bank Data, and the dataset will be analyzed using STATA to identify the optimal model for assessing the correlation between liquidity and bank performance.
In summary, the research sample comprise 30 commercial banks with 330 observations from 2012 to 2022 Consequently, the panel data used in this paper is strongly balance.
Correlation matrix
Stata can be used to identify the correlation between dependent and independent variables, with results presented in the subsequent section of this research The correlation matrix provides an initial overview of the relationships among all variables, highlighting the potential for multicollinearity, which can result in inflated standard errors and bias the sign and accuracy of estimated results (Baum, 2006) Correlation coefficients range from -1 to 1, indicating the strength and direction of these relationships.
19 variable should lie below 0.8 to encounter a significant multicollinearity problem The variables that violating this problem will be eliminated to get better model.
Estimation technique
When analyzing balanced panel data, three primary models can be employed: Pooled Ordinary Least Squares (POLS), Fixed Effects Model (FEM), and Random Effects Model (REM) Each of these models offers distinct advantages and disadvantages, making it essential to choose the appropriate one based on the specific characteristics of the data and the research objectives.
The Pooled OLS model, as described by Stock and Watson (2019), is an OLS technique that assumes constant coefficients across time and space However, its primary limitation is the inability to differentiate between various cross-sectional units, which can obscure the unique characteristics of each unit Additionally, the model is susceptible to violations due to autocorrelation errors To address these issues, both Fixed Effects Models (FEM) and Random Effects Models (REM) are recommended as alternatives.
The Fixed Effect Model (FEM) posits that each individual possesses unique time-invariant characteristics influencing the dependent variable, effectively controlling for unobserved heterogeneity, a limitation of Pooled Ordinary Least Squares (POLS) However, FEM has its drawbacks, as it is not appropriate for assessing the impact of variables that remain constant over time.
The Random Effect Model (REM) estimates the impact of unmeasurable individual-specific characteristics, assuming that the effects of independent variables on dependent variables vary randomly among individuals This approach effectively addresses the limitations of the Pooled Ordinary Least Squares (POLS) method.
20 sometime can be bias with unobserved independent variable that have relationship with both dependent and independent variables
This study utilizes three models: the Wald test or F-test for selecting between Pooled Ordinary Least Squares (POLS) and Fixed Effects Model (FEM), the Breusch-Pagan Lagrangian Multiplier test for Ordinary Least Squares (OLS) or Random Effects Model (REM), and the Hausman test for comparing FEM and REM Additionally, the Variance Inflation Factor (VIF) will be employed to assess multicollinearity among the variables Once the final model is determined, the Feasible Generalized Least Squares (FGLS) method will be applied to address issues such as heteroskedasticity.
RE vs POLS H0 = Var(μi) = 0 Breusch-Pagan Test
H0 rejected => FE H0 rejected => RE H0 rejected => FE H0 not rejected => POLS H0 not rejected => POLS H0 not rejected => not FE
Specification of variables
Description Measurement Summary of related previous papers Dependent variable
ROA Return on assets Net income / Total assets, 100%
Nishanthini and Meerajancy (2015), Adeyanju (2011), Akhater (2018), Paul et al., (2020), Malik et al., (2016), Lukorito et al., (2014), Lartey et al., (2013), Charmler et al (2018), Ibrahim
(2017), Pasiouras and Kosmidou (2007), Alper and Anbar
ROE Return on equity Net income / Total equity, 100%
The ratio of cash and cash equivalent to total assets
Cash and cash equivalent/Total assets, 100%
Charmler et al (2018), Paul et al., (2020), Alper and Anbar
Customer deposits to total assets
(Current debt + Special mention debt)/Loans to customer, 100%
Pasiouras and Kosmidou (2007), Paul et al., (2020)
Trading securities to total assets
Deposits and borrowings from other credit institutions
Deposits and borrowings from other credit institutions/Total asset, 100%
Gross domestic product growth rate
(2011) Table 3: Description of the variables used in the regression model
In this paper, liquidity is defined solely as cash and cash equivalents, diverging from previous research that typically categorized it as liquid assets The National Institute for Finance of Vietnam highlighted that 2020 marked the final year for promoting cashless payments in the country Despite the fact that 30 million individuals utilized cashless payment methods and mobile banking experienced a remarkable growth of over 200%, Vietnam, along with Thailand and Japan, remained among the top three countries with the highest cash payment rates in Asia by the end of 2022 (Bao, 2023) This indicates that cash continues to hold the highest status as a liquid asset for citizens in both developing and developed nations.
In Vietnam, banks prioritize trading securities over investment securities, utilizing excess cash for short-term trading to maximize profits This strategy allows for quick withdrawals, effectively addressing liquidity issues as they arise.
This paper analyzes the variables of customer deposits and borrowings from other credit institutions, rather than total deposits Negative internal or external news can signal instability to customers, potentially leading to situations similar to the Silicon Valley Bank crisis.
The introduction of "other credit institutions" as a variable highlights the significant deposits made by firms into banks, which can be withdrawn in critical situations Given the substantial nature of these deposits, they play a crucial role in enhancing the liquidity of banks.
Regression model
Based on other previous studies, the theoretical model for Vietnamese banks would be demonstrated as follow:
β0: the intercept of the regression model
β1, β2, β3, β4, β5, β6, β7, β8 are coefficients of explanatory variables
ε: the error term apprehending the influences of omitted variables and other factors that are not included in the model
Result – Interpretation – Discussion
Data descriptive
Table 4 presents the summary statistics for thirty banks in Vietnam, revealing an average Return on Equity (ROE) of over 9%, significantly higher than the average Return on Assets (ROA) of more than 0.7% The small coefficient of the SEC variable, with only 204 observations and a mean value of approximately 0.009%, can be attributed to the underdeveloped financial system and the nascent security market, established in 2000, which discourages banks from utilizing it for excess cash due to perceived risks Additionally, many of these banks are relatively young, having been established less than five years prior to 2012, and typically prioritize a broad range of banking services over specialization, as seen with institutions like SVB Consequently, these younger banks often sacrifice immediate profits to capture market share and sustain strong performance.
The minimum value of non-performing loans is zero, as prestigious banks exercised caution in lending practices during their early years, ensuring responsible financial support for both individuals and corporations.
A correlation matrix, as defined by Gujarati and Porter (2009), is a table that displays the correlation coefficients between variables To address multicollinearity, the correlation between any two variables should remain below 0.8, which is satisfied by all variables in Table 5 The analysis reveals that Return on Equity (ROE) exhibits a negative correlation with nearly all other variables, except for Long-Term Assets (LTA) In contrast, Return on Assets (ROA) shows a positive correlation with Debt to Equity Financing (DBFC) and Securities (SEC), while correlating negatively with the other independent variables.
Since ROA is not used to explain ROE, it will not be considered invalid
Interpretation of the regression results
Among all models, the Hausman test was used to chosen between FEM and
REM The tables below show the result of Hausman test for both ROA and ROE model which investigate the impact of the ratio liquid assets on ROE and ROA
Table 6: Hausman test for ROE model
Table 7: Hausman test for ROA model
Both models exhibit P values below 0.05, leading to the rejection of the null hypothesis, which indicates that the Fixed Effect Model is the most suitable for explaining this dataset However, both models encounter issues with heteroskedasticity To address this problem, Feasible Generalized Least Squares is implemented.
FEM – ROE FGLS – ROE FEM – ROA FGLS – ROA LIQUID1 309.3896*
Table 8: Regression result of FEM and FGLS
In the FGLS (ROE) model, 'LTA' is the only insignificant variable with a P-value exceeding 0.05, while all other variables are significant at the 0.1% level Conversely, in the FGLS (ROA) model, all variables are significant at the same level According to Baum (2006), a higher R-squared indicates a better model fit, with the FEM (ROE) model achieving an R-squared of 0.1353, meaning that only 13.53% of the variation in the response variable is explained by LIQUID1, LIQUID2, SEC, NPL, DBFC, LTA, INF, and GDP In contrast, the FEM (ROA) model performs better, explaining nearly 50% of the variation with its independent variables.
As a result, the new estimated model is specified as follow:
− 0.974389NPL − 0.8117134DBFC − 0.1664424LTA + 1.261251INF − 0.4701459GDP + 𝜀
− 0.0633432NPL − 0.0565272DBFC − 0.1507157LTA + 0.0987816INF − 0.0322546GDP + 𝜀
The analysis reveals that the independent variables consistently exhibit the same sign in both the Return on Equity (ROE) and Return on Assets (ROA) models Specifically, a 1% increase in cash and cash equivalents (LIQUID1) leads to a significant increase in ROE by over 443% and an increase in ROA by 25.12%, assuming all other factors remain constant Conversely, LIQUID2 demonstrates a negative correlation with bank performance; thus, a 1% rise in customer deposits relative to total assets results in a decrease of 0.55% in ROE and 0.042% in ROA, all else being equal.
The relationship between securities to total assets and liquidity is significant, as a 1% increase in this ratio leads to a 662% decrease in Return on Equity (ROE) and a 48.26% decrease in Return on Assets (ROA) Additionally, a 1% rise in non-performing loans results in a 0.97% decline in ROE and a 0.063% decline in ROA, all else being equal Similarly, deposits and borrowings from other credit institutions negatively impact bank performance; a 1% increase in these deposits results in a 0.811% decrease in ROE and a 0.0057% decrease in ROA The total debt to total assets ratio (LTA) significantly affects ROA, with a 1-unit increase causing a 0.15 unit decrease in ROA Interestingly, while rising inflation typically harms financial institutions, this dataset reveals that a 1% increase in inflation correlates with a 1.26% increase in ROE and a 0.098% increase in ROA Conversely, a 1% increase in GDP leads to a 0.47% decrease in ROE and a 0.032% decrease in ROA.
Overall, the FGLS result points out that liquidity has positive relationship with bank performance in Viet Nam Although the result of ROE model may sound
The analysis indicates a notable correlation between liquidity and bank performance, despite the 'unreasonable' ratios observed in cash, cash equivalents, and securities to total assets The lack of data from securities trading may contribute to the 'unreasonable' coefficient in the ROE model, and the variables utilized to assess the relationship with ROE may not be suitable for Vietnam, as evidenced by the low R-squared value of just over 13% Consequently, the findings related to ROA are deemed more reliable in this study When comparing these results to previous research conducted in other countries, noteworthy differences emerge.
32 a similar result with Paul et al., (2020), Lukorito et al., (2014), Lartey et al., (2013), Charmler et al (2018), Ibrahim (2017), Pasiouras and Kosmidou (2007) And it is opposite to Nishanthini and Meerajancy (2015) and Adeyanju (2011).
Discussion
i The impact of internal factors
Cash plays a crucial role in determining bank profitability, demonstrating a positive correlation However, excessive unutilized cash can pose significant challenges Under stable inflation conditions, central banks, such as the Federal Reserve or the State Bank of Vietnam, typically implement low interest rates to encourage lending and consumption, thereby fostering economic growth.
Chart 1: Cash asset of the U.S commercial banks
Before the global financial crisis, low interest rates encouraged banks to aggressively extend loans As noted by Turner (2023), banks continued to access funds from interbank wholesale markets to support their rapidly growing mortgage operations until early August 2007.
Many US and UK banks, including Northern Rock, opted to originate and distribute mortgages by selling the cash flows from mortgage repayments, which became known as mortgage-backed securities (MBS) or collateralized debt obligations (CDO) Prior to its collapse, Northern Rock derived only 25% of its mortgages from traditional deposits, and the Financial Services Authority (FSA) noted that while the bank's balance sheet appeared solvent, it lacked sufficient cash resources to meet payment obligations The year 2008 marked a record low for cash assets in the U.S., highlighting that banks had excessively utilized their cash by creating various financial instruments like MBS and CDOs, which they mistakenly viewed as liquid assets In Vietnam, the situation in 2008 was similar, with house prices dropping around 40% and banks facing liquidity risks, yet no bank failures occurred While cash alone does not generate profit, banks must exercise caution in its use, ensuring that excess cash is allocated to stable liquid assets such as treasury bonds after meeting reserve requirements Furthermore, it is crucial for banks to establish robust risk management systems to anticipate and respond to market fluctuations, as evidenced by the sharp increase in cash demand following the onset of Covid-19, necessitating the preparation of various scenarios regarding vaccine availability.
34 or not or the effective of the vaccine or what is the next step of the government, then decide the next action of banks to minimize the risk exposure
Customer deposits play a crucial role in enhancing bank profitability, as there exists a reciprocal relationship between the two Banks rely on customer deposits to operate effectively, generate profits, and provide quality services Conversely, a bank with a strong and stable profit margin is likely to attract more customers than one with poor performance However, research by Demirguc-Kunt and Huzinga (1999) reveals that the expansion of bank branches can negatively impact profitability While banks often seek to broaden their reach by opening more branches domestically and internationally, this strategy may not always yield the expected financial benefits.
In 2015, banks aimed to transition from traditional branches to modern retail branches for several key reasons They sought to tap into the personal financial services market, establish a robust network for handling numerous transactions, create competitive barriers, and promote their brands while expanding product offerings However, the high costs associated with opening new branches often lead to challenges, as some branches may only attract new customer deposits temporarily, resulting in operational costs that exceed the funds received While many developed countries allow citizens to deposit money at ATMs, this service remains relatively new in Vietnam, with only a few banks currently offering it.
Many banks in Vietnam are prioritizing the expansion of physical branches over enhancing digital banking services, despite the complexities involved in automating ID verification for various services This focus on traditional banking methods may hinder their ability to innovate and meet the growing demand for digital solutions.
In Vietnam, the banking sector faces intense competition, with some streets featuring up to 16 banks within a single kilometer, highlighting the need for banks to compete not only with each other but also internally Data from the Vietnam National Institute for Finance indicates that by the end of 2020, there were 280,006 POS machines and 19,525 ATMs, reflecting a 3% increase since 2019, with a nearly 17% rise in POS transactions and a 2.56% increase in ATM payments A survey by EY Vietnam revealed that 42% of banks are developing digital transformation strategies, while 28% have begun implementing these strategies into their business models, and 11% have already approved and are executing their plans This trend suggests that banks adhering to traditional branch expansion strategies may jeopardize their profitability.
Deposits and borrowings from other credit institutions are similar to customer deposits but differ in purpose and scale Institutional deposits tend to be substantial, minimizing the impact of individual branches compared to customer deposits Typically, institutions prefer banks that share similar characteristics, such as the relationship between SVB and technology firms According to Vu (2023), small and medium enterprises (SMEs) constitute 97% of total enterprises, highlighting their vulnerability due to weaker financial stability in challenging circumstances, as noted by data from the Ministry of
In the first half of 2021, the Socialist Republic of Vietnam witnessed over seventy thousand enterprises exiting the market due to the impact of Covid-19, marking a nearly 25% increase compared to the previous year This rapid withdrawal of funds from these businesses poses a significant liquidity challenge for banks Consequently, it has become crucial for banks to distinguish between viable and non-viable firms in order to foster effective partnerships and maintain financial stability.
The security market in Vietnam remains underdeveloped, prompting banks to be cautious about engaging in securities trading Official trading hours are from 9 am to 3 pm, but with a one-and-a-half-hour break, the actual trading time is nearly five hours This discrepancy with banks' operating hours (8 am to 5 pm) creates a liquidity risk; funds left in the market after 3 pm cannot be accessed in case of urgent needs A notable incident involved Saigon Commercial Joint Stock Bank (SCB), where misinformation about its shareholders led to a rush of withdrawals, necessitating intervention from the Ministry of Public Security and the State Bank of Vietnam to clarify the situation Additionally, the range of financial products is limited, primarily focusing on stock trading, with derivatives and treasury bonds representing a minimal portion of the market, as only forward and future contracts are utilized.
The Vietnamese derivative market currently faces challenges, including a limited number of investors and high initial capital requirements, as noted by the Vietnam National Institute for Finance (2022) A significant barrier for new investors is the lack of knowledge, despite the advantages of derivatives over traditional stocks To address these issues, recent government circulars propose solutions such as offering free training courses to enhance investor understanding of derivative securities Additionally, the existing five types of fees in the derivative market hinder its growth; thus, reducing these fees or implementing free transaction policies for the first two years is recommended to attract more participants Furthermore, the government encourages the development of more accessible products for investors Overall, while still emerging, this market presents opportunities for banks to maximize profits in a stable economy.
Non-performing loans (NPLs) have a detrimental impact on bank performance, a trend that has intensified in Vietnam recently According to Van (2023), Saigon Bank experienced a decline in loan quality in the first half of 2023, with NPLs rising to 441 billion VND by June, marking an 11% increase since the start of the year Notably, the proportion of doubtful debts saw the most significant rise, pushing the NPL ratio from 2.12% to 2.3% Similarly, LP Bank reported a staggering 65% increase in NPLs during the same period, reaching 5.656 billion VND, primarily driven by a 80% surge in group 5 debts, which are at high risk of capital loss Consequently, the NPL ratio relative to total customer loans escalated from 1.46% to 2.23% by the end of the second quarter.
As of the second quarter of 2023, BAOVIET Bank experienced a significant decline in debt quality, with non-performing loans rising to 1.756 trillion VND, a 58% increase since the beginning of the year Group 5 debts doubled, constituting 87% of the total non-performing loans, causing the non-performing loan ratio to escalate from 3.34% to 4.69% In contrast, AB Bank reported a pre-tax profit of 638 billion VND for the first half of 2023, down 61% year-over-year, attributed to rising non-performing loans and increased risk provisions By the end of Q2 2023, AB Bank's non-performing loan ratio was 2.86%, with all such loans backed by collateral The bank set aside 815 billion VND for credit risk provisions, nearly four times higher than the previous year Overall, non-performing loans across the banking sector in Vietnam increased by 65.1% to 5.656 trillion VND, affecting all debt categories The non-performing loan ratio rose to 2.27% in Q2 2023 from 1.49% at the end of 2022, reflecting a broader trend among banks, many of which hold collateralized loans from real estate companies that struggled to repay debts, resulting in nearly 40% of property developers declaring bankruptcy by the end of 2022.
In the first quarter of 2023, house prices in Ho Chi Minh City fell by 10% to 25%, with only 30% of land sales yielding profits, while 40% of investors faced losses (Vu, 2023) Following this, the State Bank of Vietnam inspected 11 banks for violations related to corporate bond investments and implemented new regulations to limit public fundraising activities (Ngoc, 2023) These measures have raised concerns about banks’ abilities to issue bonds aimed at debt restructuring, share acquisition, or increasing operational capital (Vu et al., 2022) As a result, the upcoming year may present significant challenges for commercial banks in Vietnam, emphasizing the need to prioritize the management of non-performing loans over merely increasing lending to enhance loan quality ratios.
According to Stern (2009), the Federal Reserve's primary focus is on controlling the inflation rate From 2022 to the present, the Fed has implemented 11 interest rate hikes, raising rates to between 5.25% and 5.5% to combat high inflation This increase in the Fed fund rate has resulted in higher interest rates for banks, limiting their ability to offer new loans In Vietnam, at the end of 2022 and early 2023, some commercial banks reported record-high deposit rates exceeding 10% (Dinh and Huong, 2023) However, in a recent announcement, the State Bank of Vietnam (SBV, 2023) noted that as inflation approaches its peak, it has reduced certain interest rates, such as the rediscounting rate from 4.5% to 3.5% and the rate for credit institutions from 7.0% to 6.0%, to support commercial banks after a prolonged period of rising rates.
Policy suggestion
This research examines the relationship between bank performance and liquidity using data from 30 commercial banks in Vietnam from 2012 to 2022 It reveals a trade-off: excessive liquidity can reduce profits, while insufficient reserves may force banks to sell assets at discounted prices Each bank must identify an optimal liquidity level to maximize profits, emphasizing the importance of timing Developing tailored risk management models is crucial for predicting future scenarios and adjusting policies accordingly to mitigate systemic risks Smaller banks can adopt models used by larger institutions to navigate unstable events, as poor performance in one bank can impact others Additionally, effective risk management enhances forecasting abilities regarding macroeconomic factors like inflation and GDP Banks should also pay attention to customer behavior and adapt to the growing trend of cashless payments by transitioning from traditional branches to modern retail strategies and enhancing services such as e-banking and mobile applications.
Since the whole world is now struggling with unstable inflation and consequence of Covid – 19 pandemic, the banks can leave the security trading sector
Addressing non-performing loans and redistributing capital flow is crucial for banks, as these loans not only generate zero profit but also incur costs for write-offs, potentially leading to bank runs due to insufficient income The challenge of balancing profitability and liquidity is a significant issue for the banking sector globally, including in Vietnam The State Bank of Vietnam (SBV) must expedite the resolution of non-performing loans and implement Basel III standards across domestic commercial banks If timely action is not taken, the SBV should enhance oversight of liquidity regulations, particularly for smaller banks prone to violations While this may temporarily slow the overall growth of Vietnam's banking system, it will promote long-term stability and mitigate potential crises Additionally, improving the SBV's forecasting model is essential to provide commercial banks with the necessary time to analyze and restructure loans effectively, ensuring safety and alignment with business operations.
Limitation and conclusion
This paper faces significant limitations, primarily due to the absence of suitable variables The Liquidity Coverage Ratio (LCR) and Net Stable Funding Ratio (NSFR) are essential metrics for assessment but are primarily utilized under Basel III standards As noted by Nguyen and Nguyen (2023), Basel III is a benchmark that banks strive to meet; however, in Vietnam, only six out of twenty commercial banks currently implement Basel III, while the rest adhere to Basel II The State Bank of Vietnam aims for all banks to adopt Basel II standards by 2025, rendering LCR and NSFR unsuitable as independent variables for this study Additionally, there is a lack of comprehensive data to create a larger sample size, as some banks' quarterly data is limited and cannot be verified against consolidated financial statements, necessitating annual data collection.
This study analyzed the influence of liquidity on the performance of commercial banks in Vietnam from 2012 to 2022 It found that liquidity, measured by the ratio of cash and cash equivalents to total assets, positively affects bank performance Specifically, a 1% increase in liquidity (LIQUID1) correlates with a 25.12% rise in Return on Assets (ROA), holding other factors constant, while the impact on Return on Equity (ROE) is also noteworthy.
This paper advises against using Return on Equity (ROE) results for future references due to their unreliability It highlights current issues faced by Vietnamese commercial banks, including an excessive focus on expanding branch networks at the expense of enhancing online services, a rise in non-performing loans, and inefficient capital flow To address these challenges, the paper proposes several solutions for improvement.
To enhance the long-term profitability of Vietnam's banking sector, it is crucial for both commercial banks and the State Bank of Vietnam to adopt tighter liquidity policies, even if this means sacrificing a small amount of short-term profit.
Appendix
Chart 1: Cash asset of the U.S commercial banks
Chart 2: Viet Nam GDP growth rate
Table 10: Breusch – Pagan Test for heteroscedasticity
51 Table 15: Feasible Generalized Least Squares Model
55 Table 22: Feasible Generalized Least Squares Model