MINISTRY OF EDUCATION & TRAINING THE STATE BANK OF VIETNAM BANKING UNIVERSITY HO CHI MINH CITY TRAN HUYNH THANH HUY THE IMPACT OF INCOME DIVERSIFICATION ON PROFITABILITY AND RISK OF VIThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banksThe impact of income diversification on profitability and risk of Vietnamese commercial banks
INTRODUCTION
Rationale of the study
It is likely apparent to say that commercial banks are the most important intermediary financial institutions in the market economy because if the banking system did not exist, it would be a troublous sequence in the market economy In addition, commercial banks are the most appropriate institutions to implement the monetary policies from Central Bank, helping the macro economy as well
According to DeYoung & Roland (2001), since the XXI century, it is global tendency to diversify banks due to competitive pressure or being attracted by profit from financial activities In addition, in a period between 2006 – 2007, an explosion of stock market as well as investment operation generates a large amount of returns for participants Therefore, more and more financial institutions have established many subsidiaries to gain as many as returns in financial environment That is a reason why Vietnamese commercial banks focus more in this diversification tendency which pay more attention on investing on non-interest income generating activities, diversifying business fields, products, and services, while traditional activities are too risky and unstable However, according to McKibbin & Fernando (2021), some global crisis has challenged seriously the global economy with the latest crisis - the Covid-19 pandemic According to Le et al (2022), it is worth noting that the banking sector's profitability may decline while the associated risk may rise during epidemic periods due to measures such as social distancing, lockdowns, heightened unemployment, and business closures
According to traditional operations, credit activities is a main source generating revenues in the bank, but credit activities are uncertain and risky That is a reason why in reality, many banks went bankruptcy due to their bad debts With non-performing loans ratio exceeding the permitted level of 4-5%, commercial banks are no longer lucrative and gradually lose their own capital Moreover, according to some previous stastistics, incomes generating from traditional activities of most commercial banks in the world took up two thirds of their total incomes, while it generates approximately 90% of income of Vietnamese commercial banks
Furthermore, incomes of most Vietnamese commercial banks are generated from credit acitivies that are known as risky ones Hence, Vietnamese commercial banks are necessary to shift to different activities in order to reduce risk pressure on banks Besides, according to Feyen et al (2021), with the Covid-19 pandemic, financial principles, policies, as well as traditional operation have currently faced many challenges, and therefore, banks around the world have been implementing a variety of measures about income diversification to minimize financial difficulties in the market
Besides, it is fiercer competition among banks since foreign commercial banks are allowed to open 100% foreign owned banks in Vietnam as well as the number and size of financial institutions have increased significantly recently This competition has made the marginal income more narrow generating from credit activities If financial institutions with main incomes from credit activities want to survive, develop, achieve higher profit, and construct a stable position, they should diversify types of services to keep income stable
Research on the impact of income diversification on the profitability of commercial banks is conducted worldwide, with variations observed in different regions, and Vietnam is no exception In Vietnam, certain studies have suggested that a higher degree of income diversification is associated with increased profitability For example, Vinh & Mai (2015) conducted an analysis of 37 commercial banks in Vietnam from 2006 to 2013, concluding that banks engaged in a wider range of operational activities tend to achieve greater profits Conversely, banks relying heavily on income diversification may experience a reduction in risk- adjusted profitability The empirical findings from their research challenge the notion that income diversification universally benefits commercial banks in the Vietnamese context Furthermore, another study conducted by Le et al (2022) explored the imcome diversification influencing the risk of Vietnamese commercial banks during the period of non - Covid-19 pandemic and Covid-19 pandemic from 2012 to 2020 The results indicated that an increase in income diversification corresponds to a decrease in the risk of default Additionally, the research outcomes highlighted the research observed a tendency for the default risk of banks to decrease amid the outbreak of the COVID-19 pandemic
The question of whether income diversification in recent years has yielded the potential and optimal advantages for Vietnamese commercial banks, and how to effectively implement income diversification to ensure a stable increase in profits and a reduction in risk, is a matter that warrants in-depth research However, in Vietnam, there is a limitation of studies that comprehensively investigate the impact of income diversification on the profitability and risk management of Vietnamese commercial banks Moreover, the COVID-19 pandemic has compelled banks to undertake various measures to minimize its shadow over multiple economic dimensions including encompassing business closures, limited growth opportunities, and placed immense pressure on enterprises grappling with their debt obligations Furthermore, due to government-mandated forbearance regulations, the pandemic has induced an economic downturn, exerting pressure on the lending activities of banks Additionally, due to the "Restructuring of Credit Institutions for Bad Debt Resolution in the 2021-2025 Period," as approved by the Prime Minister via Decision
No 689/QĐ-TTg on June 8, 2022, Vietnamese commercial banks are actively working on diversifying their income sources This involves venturing into non- traditional sectors and expanding their traditional activities, such as capital mobilization and lending, to generate income beyond interest, further enhancing income diversification
Hence, to address this concerning issue, the author decides to choose the topic:
"The impact of income diversification on profitability and risk of Vietnamese Commercial Banks".
Research objectives
The overall objective of the study is to research and analyze the impact of income diversification on the profitability and risks of Vietnamese commercial banks over period between 2012 – 2022 Then, the author will make some recommendations to improve business performance of Vietnamese commercial banks
• Evaluating the impact of income diversification on profitability of commercial banks in Vietnam including the Covid-19 pandemic
• Evaluating the impact of income diversification on the risk of commercial banks in Vietnam including the Covid-19 pandemic
• Making some recommendations for commercial banks to implement income diversification effectively to increase profitability and minimize risk of Vietnamese commercial banks.
Reseach questions
In line with the objectives highlighted above, the two specific research questions were formulated as follows:
• Research question 1: How does income diversification affect profitability and risk of commercial banks in Vietnam including the Covid-19 pandemic over the period of 2012 to 2022?
• Research question 2: What recommendations can help improve the profitability and minimize risk as diversifying income for Vietnamese commercial banks?
Research scope
This thesis focuses on researching the impact of income diversification on the profitability and risk of commercial banks in Vietnam Research scope is limited to
29 joint stock commercial banks which are listed banks The analysis period from
2012 to 2022 This phase is very important and sensitive because it occured many debt restructuring reforms Vietnamese credit institutions.
Research method
Based on reviewing theories related to research issues, the study uses quantitative research method and regression with panel data to analyze some factors, including income diversification factors affecting risk and profitability of Vietnamese commercial banks Specifically, to overcome the latent endogenous phenomenon in the model as well as to present a better objective result, the study also uses the Generalized Method of Moment (GMM) estimation method (based on Arellano & Bover , 1995 and Blundell & Bond, 1998) Besides, in this study, the author uses a sample data of 29 commercial banks in Vietnam from 2012 to 2022 in audited financial statement from Bankscope data source.
Significance of the research
In practical terms, according to the latest data, the analysis of how efficiency the income diversification affects the profitability as well as risk of commercial banks in Vietnam provides banks an overview of the impact of income diversification on profitability as well as risk during the period of non - Covid-19 pandemic and Covid-19 pandemic Hence, it may be essential to help banks to make recommendations, suggestions as well as greater approaches which is appropriate with strategies, plans for the operation in bank in the coming time
In theoretical terms, the results of this study provide empirical evidence about impacts of income diversification on banking performance during the period of non
- Covid-19 pandemic and Covid-19 pandemic.
Research structure
The study will be presented in five chapters as follows:
In this chapter, the author will not only highlight the importance of the topic within the current context but also bring attention to key concerns that will be explored This section will encompass elements such as the scholarly basis for the research issue, elucidation of the research topic's objectives, and the formulation of research questions designed to fulfill these objectives.
LITERATURE REVIEW
Theoretical framework
There are many definitions about commercial bank in different aspects, nevertheless, in general, according to Peter S Rose (2002), a commercial bank is to sell deposits and make loans to individuals and coporations, is defined as a type of bank which may conduct all banking operations and other business activities in the purpose of profit In addition, the commercial bank accepts deposits such as demand deposits, time deposits, savings deposits, and deposits of other types; provides for customers payment instruments, payment services including international payment services and domestic payment services such as check, payment order, and collection; lending service; and offers fundamental financial products to individual customers and small businesses
Some specific characteristics are included as follows:
• Business activity in banking is a regular business and provision of one or several operations such as receiving deposits, extending credit, or providing payment services via accounts
• Operations of commercial banks have the following characteristics: Conditional business, financial assets which is the fundamental objects of banking business, banking operations as intermediaries, highly significant impact on environmental by banking operations, or high risk
In basic words, profitability holds significant importance in gauging the operational efficiency of a commercial bank According to Don Hofstrand (2009), it stands as the primary goal for all business endeavors, and a lack of favorable profitability makes long-term sustainability challenging As outlined by Ezejiofor (2017), profitability refers to a firm’s capacity to generate profits from its business operations The effectiveness of profit generation relies on how adeptly managers utilize the available market resources Olalekan & Adeyinka (2013) contend that the ability to generate profit for a commercial bank signifies its ability to efficiently conduct business operations and yield profits for the institution
According to Olweny & Shipho (2011), the Efficient Structures (ES) theory, in relation to profitability, suggests that commercial banks aim to achieve efficient resource allocation and organizational structures to enhance their profitability By minimizing transaction costs and optimizing their internal organization, commercial banks can improve their overall financial performance including cost minimization, internal efficiency, long-term performance, … leading to higher profitability While the ES theory provides insights into how efficient organizational structures can impact profitability, other factors such as market conditions, competitive dynamics, and strategic decision-making also play significant roles in determining a commercial bank's profitability
Thus, the ability to generate profit can be interpreted as the level at which a bank creates earnings through the sensible and efficient utilization of its existing resources Additionally, this profitability forms the cornerstone for the achievement of a bank's business goals and enhances its operational effectiveness A high profitability empowers the bank to establish a strong reputation in the market and gain a competitive edge, making it more attractive to investors and facilitating investments in infrastructure and other advancements
Indicators to measure the profitability of commercial banks
In financial sector, there are many indicators to measure and evaluate how efficiency the banking performance is Therefore, according to many studies from various famous researchers, the most important and effective indicators used commonly to evaluate the profitability of commercial banks are return on assets (ROA) and return on equity (ROE) Utilizing these indicators is a better approach for managers to understand deeply the current health of financial performance as well as the financial capacity of the bank, consequently, it is possible to restructure the business operations in accordance with the internal characteristics of the bank and lead to be sustainable development, better competition
Return on Total Assets (ROA) is an indicator reflecting the ability of the bank as generating profit by investing in asset through an after-tax profit from an asset of a commercial bank According to Dietrich & Wanzenried (2010), the ROA indicator points out the comparison between net profit and total assets and clarifies how many profitable coins generates by investing a coin per an asset In the other words, the higher value the ROA is, the more quality the assets bring In addition, Molyneux & Thornton (1992) said that the one of a crucial aspect for the use of bank profit assessment and studies is ROA This is because ROA shows how efficiency an asset of a bank is invested If a bank has a low ROA, lending policy is ineffective, or the costs of the bank is overvalued ROA is calculated as follows:
Return on equity (ROE) is an indicator reflecting how efficiency the capitalis used through the profit after tax achieved by an equity According to Rose Hudgins (2010), the ROE indicator represents the comparison between net profit and equity
In other words, it means how many coins in banking profit is generated by a coin per a capital The higher value the ROE is, the more effective performance the commercial banks employ the owner's equity
Following some previous studies, the author points out that using the ROA and ROE ratios to evaluate the bank's business performance and showing the ability of owners to recover their investment capital is a common and efficiency approach with managers And according to the Moody standard about financial capacity, two indicators are evaluated well in the frame: ROA ≥ 0.01, ROE ≥ 0.12 - 0.15
In conclusion, using ROA and ROE indicators are common and effective to present an operating business efficiency Therefore, it is reliable to show the expression of the profit measurement variable in a simple way, moreover, it is easy for researchers to use ROA and ROE indicators as the dependent variable in the model represents the profitability of commercial banks
At first, risk is a general term which is familiar in the economic sector in general and finance in particular However, each economist or each financialist has its own definition Generally, according to many previous studies, risk definition can be divided into two points of view
With traditional aspect, it is a negative meaning about a loss or a danger when risk is concerned In a fundamental way, risk is considered as something that is not beneficial, suddenly happens, and even can not be foreseen In business sector, risk is defined as a loss of assets, a decrease in the real profit compared to the expected return Consequently, risk can be viewed as uncertainty in the business process or a health problem in business operation that has a significant impact on the existence and development of each firm
With the modern aspect, it has a both positive and negative meaning when risk is considered as a measurable loss, an uncertainty of the future outcome of business operation It can be meant that risk can bring losses, however, they can also have benefits and opportunities to operation That is a reason why, in business operation, managers can rely on risk to seek profit as much as possible
Following to the modern aspect, many economists also have definitions of risk in different ways Specifically, according to Knight (1921), who is an American economist, he showed that risk is uncertainly measured Besides, Irving Perfer defines as risk can be measured by probability about its randomness With in banking sector, according to Peter S Rose (2002), it is similar some author above when he said that risk is the uncertainty degree of some events or as losses in banking operations affecting seriously to the banking performance
RESEARCH METHOD AND DATA
Research method
Quantitative method is the main research method in this study According to Kothari (2004), based on numerical measurement, quantitative research is applied to issue which can be expressed numerically, and involves testing theory and hypothesis through inference process Hence, it is possible to state that quantitative research is research method using many different methods to measure, reflect and discuss the relationships among relevant variables Quantitative research usually aims to test hypothetical models derived from previou theories and its results show the authors an overall view about the topic as well as additional result to that theory In addition, a firm can be beneficial from quantitative method as bringing and providing a scientific basis for solving practical problems
According to quantitative research, it is required to have overall descriptive statistics if the author wants to be an overview and accurate assessment of the indicators and data in the study After the steps involved in data collection have been performed, the Stata 15 software can be used to provide the results of descriptive statistics including the common types of descriptive statistical as follows
Table 3.3 Types of descriptive statistics
1 Mean The average value of all variables
2 Maximum The maximum value in the list of variable value
3 Minimum The minimum value in the list of variable value
4 Standard deviation The measure of the degree of dispersion around the mean
Generalized Method of Moments (GMM)
In the study of panel data by a traditional way, researchers almost apply the fixed effects or random effects in estimating research models In the case of the detecting negative problems leading to inaccurate estimation (defected model), the cause of the defection is originated from functional error or omission of important variables Besides, many previous studies on the topic of profitability and risk related to income diversification have some defects To address these defects, this research employs a dynamic panel data model that includes lagged variables of the dependent variable This approach may introduce endogeneity due to the correlation with the error term Furthermore, because of the simultaneous relationship between independent and dependent variables, the research model may also experience endogeneity Additionally, the decision to diversify can be influenced by past and current business performance, potentially leading to autocorrelation and heteroscedasticity in the model's variables Therefore, to solve the problems when encountering this defect, Hansen (1982) developed additional instrumental variables (closely related to the lagged independent, dependent variable in the old model) And using Generalized Method of Moments (GMM) model is appropriate
Considering a relationship, with a dependent variable, Y, and an explanatory variable The model can be modified as follows:
Thus, the extended model can be shown as:
𝑌 𝑖𝑡 = 𝛽 1 𝑌 𝑖,𝑡−1 + 𝛽 2 𝑋 𝑖𝑡 + 𝛾 𝑖 + 𝜀 𝑖𝑡 Where 𝜇 𝑖𝑡 = 𝛾 𝑖 + 𝜀 𝑖𝑡 is the composite error 𝛾 𝑖 , 𝜀 𝑖𝑡 represent idiosyncratic disturbances
To clarify the reason why GMM estimation method is used, it is essential to determine an endogeneity problem first Having a lagged dependent variable as well as explanatory variables in the calculation above implies that the estimators of biased coefficient will be tested by Ordinary Least Squares (OLS) This is a result of possible correlations among these lagged variables In addition, the more presence the individual effects will have, the more bias the auto regressive OLS estimators will be (Hsiao, 1986) Consequently, according to Arellano & Bover (1995) and Blundell & Bond (1998), the GMM estimator method should be employed to solve this endogeneity bias These authors constructed this method through combining two set of equations The difference among lagged indespendent and dependent variables, and both independent and dependent variables in levels are expressed by the first equation and the second equation, respectively
𝑌 𝑖𝑡 = 𝛼 1 𝑌 𝑖,𝑡−1 + 𝛼 2 𝑋 𝑖𝑡 + 𝛾 𝑖𝑡 + 𝜇 𝑖𝑡 Where 𝑌 𝑖𝑡 measures the insolvency risk (Zscore), for each bank i in time t
𝑌 𝑖,𝑡−1 measure observed in the prior period 𝛾 𝑖𝑡 represents idiosyncratic disturbances and the error term 𝜇 𝑖𝑡 is independent across banks 𝑋 𝑖𝑡 is a vector of additional and explanatory variables (HHI_REV, L_A, SIZE, ASSET_GRO, DPS_TA, GL_GRO)
Instead of another different the estimators to remove fixed effects, System- GMM creates them uncorrelation with the fixed effects This way is more suitable beacause of some reasonable reasons Firstly, the explanatory variables’ changes in the past, for instance, performance evaluation will predict better of present levels than past change in levels Secondly, System-GMM is possible to have time- invariant regressors for example specific regulatory and institutional adequacy controlling in the method Thirdly, System-GMM is more appropriate to address omitted data due to the presence of lagged observations in the equation Besides, this method estimates the standard error improving heteroskedasticity with a windmeijer correction, which is a finite sample correction in GMM estimators Since the precision of the System-GMM method is extremely influenced on the assumption without correlation in the idiosyncratic disturbances, Roodman (2009) indicates that it should include time dummies in the estimators Futhermore, Blundell & Bond (1998) tested and confirmed that System-GMM has smaller variance and is more efficient, thus improving the accuracy of estimation Finally, although there are two types of GMM methods: the Difference GMM (D-GMM) and the System GMM (S- GMM), the data source spans a shorter period (11 years) compared to the number of banks (29 banks) Therefore, the use of the System GMM method is more optimal in this case
Reporting diagnostic tests: Firstly, according to Roodman (2009), to avoid the problem that the model has too many instruments in the regression, and it leads to lose the power of the tests, the study will limit the instrumental variables, which means the number of instrument variables generated should not exceed the number of observation banks Secondly, Hansen test is used to test the over-identifying of instrumental variables because Hansen test in 2-step estimation could be more efficient than Sargan test in 1-step estimation (Roodman, 2009) This test determines a correlation between the instrument variable and the residual in the model through testing the hypothesis H0: the instrument variables are appropriate (fully completed over-identifying) Accepting the hypothesis H0 (p-value > ) means that the instrument variables used in the model are suitable Finally, it is necessary to perform second-order autocorrelation test (AR2) to determine the second-order correlation of residual in the model Hypothesis H0 of the Arellano-Bond tests will be no second- order autocorrelation of the residual The study requires that p-value is bigger than the alpha () so that the hypothesis H0 cannot be rejected In other words, the residual of the model does not exist second-order autocorrelation, consequently, the model is appropriate.
Research model
Profitability and risk are fundamental concept in finance and banking sector
In banking, riskier activities can boost profits but also increase the chance of losses Therefore, profitability and risk have a close relationship in banking management and operations According to the study of Sanya & Wolfe (2011), Vinh & Mai (2015) and Le et al (2022), with a view to investigating the correlation between profitability and risk from income diversification of the commercial banks, author uses the research model as follows:
• Profitability is presented by ROAA, ROEA
• Risk is presented by ZSCORE
• HHI_REV represents income diversification
• L_A, SIZE, ASSET_GRO, DPS_TA, GL_GRO, COVID are controlling variables.
Variables
The reason why author constructs two models is that author would like to analyze the relationship between profitability and risk from income diversification Consequently, author measures through Profitability and Risk
It is an indicator determined the bank profit and measured as another two ratios, which are ROAA and ROEA at the end of year t of bank i ROAA indicates of how profitable a firm is relative to its total assets In addition, it shows how efficient a management of each bank to utilize its assets to generate revenues Chiorazzo et al (2008) and Lee et al (2014) all state that ROAA is calculated by the earnings after tax to the average of total assets in consecutive 2-year of the bank at the finally financial year The other indicator is ROEA called return on average of the total equity ROEA represents for how lucrative a firm is relative to its total stockholder’s equity Moreover, how effective a management of each bank to utilize its equity to generate revenues Lee et al (2014) and Trujillo-Ponce (2013) describe that it is calculated by by the earnings after tax to the average of total stockholder’s equity in consecutive 2-year of the bank at the finally financial year
As mentioned above, the other dependent variable in the empirical models is risk It stands for how loss the diversification affects to bank income In this study, the author chooses a typical indicator to analyze risk: ZScore ZScore representing for insolvency risk of banks measures a stability of bank income and has an inverse proportion to default probability of a bank What I mean is that the higher value the ZScore is, the lower value the risk is
About the measure of insolvency risk, Z-score, Boyd & Graham (1986), and Z-score in the Altman (1968) had a different measure According to Altman (1968), his study run the Logisitic Regression Model with 5 variables to predict the bankruptcy The Z-socre in its range can conclude that the firm will proceed bankruptcy or not In addition, with credit risk management at the banks, this indicator considers as a health assessment score of the borrowing firm
However, in this study, the author would like to mention the Z-score created by two authors – Boyd & Graham (1986), which is used specifically for measuring the insolvency risk probability of financial institutions or commercial banks
In 1986, Z-score was created with original formula as follows:
𝜎 𝑅𝑂𝐴𝐴 Z-score is aimed at measuring insolvency risk of all kinds of the banks The higher value the Z-socre is, the lower insolvency risk the banks have
From 1986 until now, insolvency risk formula has changed a lot to adapt with each author research However, many studies are often used Z-score formula of Cihak & Hess (2008) (cited in Kha (2017)) for stability quantification and calculated:
𝜎 𝑅𝑂𝐴𝐴 Afterwards, the author follows Z-score formula of Cihak and Hess (2008) (cited in Kha (2017)) in this study The reason why we decide to choose Cihak & Hess formula is that calculating independently the average value of ROA and the ratio of equity to assest means that it makes the measures more exact and more effective than the others
In this study, diversification activities are considered through bank income construction including interest income and non-interest income If the bank revenue is merely derived from net interest income, the bank seems to be concentraded
Whereas banks whose net income consists of net interest income and non-interest income is considered diversified According to Asif & Akhter (2019), there are some calculation about income diversification such as a ratio of non-interest income, the Herfindahl Hirschman Index (HHI), , and among these, nearly 30% of previous studies use the Herfindahl Hirschman Index to evaluate the degree of income diversification of banks However, the Herfindahl Hirschman Index is more widely applied by authors in measuring the concentration level of bank revenue sources Therefore, this study uses this index to analyze and measure income diversification of banks Specifically, following Elsas et al (2010), Gurbuz et al (2013), Sanya & Wolfe (2011) and Mercieca et al (2007), in order to account for diversification between two fundamental components above, the independent variable in this study chosen to represent for bank diversification activities is Herfindahl Hirschman Index (𝐻𝐻𝐼 𝑅𝐸𝑉 ), whose ratio is measured the change of bank income This indicator is calculated as follows:
𝑁𝐸𝑇𝑂𝑃 ) 2 Where NON is non-interest income measured as a total amount of net comission income, net income from trading activities including foreign currencies, securities and investment securities, net other income and capital contributions & equity investments income; NET is net interest income measured as interest income minus interest expenses; NETOP is net-operating income defined by a sum of net interest income and non-interest income through formula NETOP = NET + NON A gap of 𝐻𝐻𝐼 𝑅𝐸𝑉 is around 0.5 to 1.0 𝐻𝐻𝐼 𝑅𝐸𝑉 value equaling at 0.5 means that the bank is completely diversified, while at 1.0 𝐻𝐻𝐼 𝑅𝐸𝑉 value indicates the least diversification income Therefore, Mercieca et al (2007) as well as Stiroh (2004a) & Stiroh (2004b) outline that the higher ratio the 𝐻𝐻𝐼 𝑅𝐸𝑉 is, the more concentration and the less diversified income the bank becomes
In Vietnam, for over a decade, commercial banks have kept pace with a global tendency, which is a diversification Therefore, a bank not only operates traditional activities, it also diversifies more in products and services To be diversified legally, many banks have established subsidiaries to specialize in each segment (insurance, securities, or valuation) This shows that it is highly and positively determined to integrate a bank into the world through shifting traditional income to non-interest income in the operational structure of commercial banks Therefore, the author expects that income diversification will have a positive impact on increasing profit (ROA and ROE) and reducing risk of commercial banks
Besides, a controlling variable is also an important elements of research model It aims at clearly identify the relationship between a dependent variable and an independent variable Moreover, with small variations in model, it may have significant impacts on the outcome being measured
Specifically, the author lists all the controlling variables appeared as well as affected considerable to our model below:
Firstly, a leverage ratio (𝐿_𝐴 𝑖𝑡 ): This is measured of total loans to total assests DeYoung & Roland (2001), DeYoung & Rice (2004), Stiroh (2004b) and K J Stiroh
& Rumble (2006) point out that this ratio represents for debit balance of bank i in year t and reflects how financially stable a bank is A more risk-tolerant bank will make more loans to have an outpace growth of the profitability of loans to the assets However, the higher ratio causes to increase illiquidity, consequently, leading the banks to face some common risk such as liquidity risk In addition, to increase profit, this is also an important factor, nevertheless, the increase in outstanding loans also leads to increase risk and reduce profit This ratio indicates an increase in lending, which can affect the liquidity of the bank as it leads to reduces the amount of cash holdings the bank This opinion was confirmed in some studies such as Vinh & Mai (2015), DeYoung & Roland (2001), DeYoung & Rice (2004) Consequently, many studies point out that debt ratio has a negative impact on profitability and has a positive impact on risk
Secondly, a bank size (𝑆𝐼𝑍𝐸 𝑖𝑡 ): It represents for the size of bank i in year t and is measured as the natural logarithm of total assests of bank Bank size is understood as an advantage of size, meaning that the larger banks will generate more profit than smaller banks because they are more competitive advantage due to more branches, or generating more economic benefits Hence, the large banks are no longer worried and afraid about the bankruptcy because their strategies are willing to allow high- risk credits to be signed for the purpose of improving profit According to Sanya & Wolfe (2011), Vinh & Mai (2015), Chiorazzo et al (2008), these studies also had a result that larger banks may have better opportunities for risk management and diversification, while smaller banks are more flexible in their operations Besides, following the theories mentioned above, these theories indicate that the relationship between the size and the returns is related positively to income diversification However, it is more serious if the risk management is low Especially, too large-scale expansion can affect cost management, which also affects the profitability of the bank As a consequence, according to many previous studies, it is both positive and negative impact of size on profitability, nevertheless, positive direction outweighs negative one
Thirdly, an asset growth (𝐴𝑆𝑆𝐸𝑇_𝐺𝑅𝑂 𝑖𝑡 ): This indicator calculated by the growth ratio of total assets in a current year to total assets in a previous year is measured the growth of assets of bank I in year t It stands for controlling the effect of expansion strategy on profitability as well as insolvency risk (Lee et al., 2014; Sanya & Wolfe, 2011) Moreover, banks with a fast growth can bring better business efficiency leading to increase business efficiency Based on the portfolio diversification theory, a high asset growth rate typically indicates that a bank is expanding its operations and investing in new assets Income diversification helps reduce risk by not relying solely on one type of asset or income source This can enhance profitability if the new assets are managed efficiently and allocated appropriately According to Chiorazzo et al (2008), Stiroh (2004b), the author stated that at the same time, banks with a fast growth may also be accompanied by the rapid increase of risk, because the increase in profit may be not equal the increase of the risk Therefore, based on the theories above and some previous studies, the ratio is expected to be positive to profitability and bank risk
RESEARCH RESULTS
The reality of income diversification on profitability and risk at vietnamese
Commercial banks are the most important financial intermediaries in a market economy because, without the banking system, a series of disruptions would occur in the market economy However, like other sectors in this economy, increasing demand and competition, along with rising customer expectations, have forced banks to change their operational strategies, such as expanding activities and diversifying income by developing new services alongside traditional business activities Picture 4.1 below shows the income diversification and the profitability of Vietnamese commercial banks from 2012 to 2022
Picture 4.11 The income diversification and profitability of Vietnamese commercial banks 2012 - 2022
Source: Author’s summary Picture 4.1 shows that Vietnamese commercial banks experienced an increase in income diversification from 2012 to 2022 Specifically, over the 11-year period (from 2012 to 2022), the HHI_REV index decreased from 0.94 in 2012 to 0.67 in
2022 Although there was a slight increase in the HHI_REV index in 2015 (0.80) and
2022 (0.67), overall, the banks’ income sources became relatively well-diversified over the 11 years Regarding banking profitability, the ROA and ROE ratios showed positive upward trends from 2012 to 2022 Specifically, the average ROA increased
ROA ROE HHI_REV from 0.8% in 2012 to 1.4% in 2022 Similarly, the average ROE changed from 7.7% in 2012 to 15.7% in 2022 This indicates that banks are tending to improve their profitability through diversified income sources
However, the expansion and diversification of income sources have impacted risk, with variations across different years Picture 4.2 below provides an overview of the income diversification and the risk at Vietnamese commercial banks from
Picture 4.12 The income diversification and risk of Vietnamese commercial banks 2012 - 2022
Source: Author’s summary Picture 4.2 shows the fluctuating of ininsolvency risk among Vietnamese commercial banks Specifically, from 2012 to 2020, the Z-Score index decreased from 33.2 (in 2012) to 21.2 (in 2020) However, the index increased in 2021 and
2022 to 32.2 and 28.2, respectively As the Z-Score index increases, it indicates a lower risk of insolvency for the banks Additionally, Figure 4.2 also shows that the relationship between income diversification and risk has not changed correspondingly, as seen in the relationship between income diversification and profitability However, the growth in the Z-Score index during the last two years of the study period, along with increased income diversification, indicates a positive trend in enhancing income sources and reducing risk in commercial banks
Descriptive statistics
From the theoretical framework and empirical studies, the study will present a research model on the main factors impacting on risk and profitability of commercial banks in Vietnam Next, the study will use the collected panel data to construct the model and draw out how to affect risk and profitability at commercial banks in Vietnam by using Stata 15 software
According to the table 4.1, an average ROA in the sample of 0.84% The bank with the highest ROA is 3.65%, while the bank has the lowest ROA of 0.00% The average ROE value is 9.93%, specifically, a commercial bank has the highest ROE of 30.33%, whereas the bank with the lowest ROE is 0.00% ROA ans ROE results show that while ROA has a small difference between banks with the highest ROA and the banks with the lowest ROA, ROE has an inverse comment as a large difference between banks with the highest ROE and the banks with the lowest ROE
In terms of risk, ZScore of Vietnamese commercial banks in the data sample measuring the insolvency risk of banks, has an average value of 27.1390, whose minimum value is 1.1527 and maximum value is 324.8641 The standard deviation of this coefficient is 25.7501, which shows that the difference is quite large in terms of risk between banks over the years
The income diversification indicator of Vietnamese commercial banks in the study (HHI_REV) averaged 0.7315 (compared with the lowest value of 0.5), showing that the diversification rate of Vietnamese commercial banks is at an average level In addition, the difference in the degree of income diversification among banks over the years is not large (standard deviation is 0.3071) However, banks are almost not diversified with HHI_REV indicator of 0.5 and banks are almost completely diversified with HHI_REV indicator of higher than 1.0 Consequently, HHI_REV indicator points out that Vietnamese banks are concerned with both net interest income and non-interest income, however, they focus more slightly on net interest income generating bank activities over the data sample Even more concentration on net interest income non-interest income may not be underestimated due to the maximum value of HHI_REV is 0.9987
The SIZE variable represents the size of the bank with the lowest value of 16.402 and the highest value of 21.4750 In addition, the mean of SIZE is 18.7785 with a standard deviation of 1.1888 SIZE variable indicates the size between the banks in the sample is not much difference
Regarding the ASSET_GRO variable, the average value of asset growth in Vietnamese banks during the period 2012 – 2022 is comparatively high (0.1794) The standard deviation is 0.5297, the highest value is 9.2381 as well as the lowest value is -0.3924 It can show that the banks implemented a potential monetary and fiscal policy to stimulate the economy after the 2007 – 2009 economic crisis The higher value the asset growth is, the better result of Vietnamese economy responses
Variable Obs Mean Std Dev Min Max
Source: Stata 15 software Regarding the gross loans growth rate (GL_GRO), its average value is 0.1972 with a standard deviation of 0.2668, which is a moderate growth in overall The lowest value and the highest one are -0.7886 and 3.8588 respectively Their high value of this indicator represents for recovering as well as being stimulated the supply and demand power, consequently, leading to develop the economy more and more Nevertheless, similarly to the loan’s ratio, higher gross loans means that the banks may have to confront with some risk, typically is liquidity risk or bankruptcy
In contrast with gross loans growth rate (GL_GRO), the deposits growth rate (DPS_TA) has an average value around 0.6509, which is extremely higher than GL_GRO The positive gap between the deposits growth rate and the gross loans growth rate means that it reduces the pressure on liquidity as well as market interest rates In addition, better growth of deposits may help the banks decrease and manage some implicit risk, which is harmful to the bank system due to an unequality between size growth and improvement of efficient risk management Furthermore, this indicator ensures a balance of using capital of Vietnamese banks
L_A variable has the mean of a little higher than 50 percent around 0.0722 (0.5722) with a standard deviation of 0.1228 which may determine that almost Vietnamese banks are loaned up Besides, the highest value and the lowest value are 0.7881 and 0.0696 respectively Moreover, this ratio indicates that these banks seem to be lower liquid and face to higher defaults
COVID variable represents the year occurring the Covid-19 pandemic with 2 value 0 and 1 In addition, the mean of COVID is 0.1818 with a standard deviation of 0.3863 COVID variable indicates with the model data, the number of years occurring the crisis is relatively small.
Correlation analysis
With a correlation, it is a statistical measure used to investigate the strength of linear relationship between two quantitative variables To put it simply, it is a popular instrument determining how simple variables are related Correlation coefficient takes a value in the range from -1 to 1 The purpose of this test is to test the probability of multicollinearity appearance between the variables above in the empirical models The author considers the correlation coefficients between pairs of independent variables presented in Table 4.2 in this study According to Gujarati (2004), if the coefficient correlation between the independent variables exceeds 0.8, it is likely to lead to high multicollinearity in the model A result shows that it does not have a pair of variables whose absolute value is higher than 0.8 The maximum of an absolute value is 0.5476, however, it is smaller than 0.8 and it interpret as the moderate correlation The other pairs of variables are negligible and low correlated As a result, we come up with a conclusion of testing correlation coefficient between the variables that a probability of multicollinearity appearance in two researching models is not strong because almost correlation of the variables has a slightly small value (around -0.30 and 0.30) Therefore, there is no multicollinearity phenomenon affecting seriously the estimation of model
Table 4.2 Correlation coefficient matrix between variables
In addition, the study also retests the multicollinearity phenomenon by the multicollinearity with VIF According to Hair et al (1995), these authors demonstrate that VIF indicator lower than 10 does not exist the multicollinearity phenomenon Therefore, following table 4.3 below, the results show that the multicollinearity with VIF has an average value of 1.27, ranging from 1.02 to 1.59, which means there is a very low correlation between the variables, consequently, leading not to occur multicollinearity phenomenon
CONCLUSIONS AND RECOMMENDATIONS
Conclusions
The research's primary objective is to evaluate the influence of non-interest income and the proportion of non-interest income components within total operating income on the risk levels of 29 banks in Vietnam spanning the period from 2012 to
2022 The study offers an up-to-date analysis of the recent financial activities of Vietnamese commercial banks, underscoring the favorable impact of income diversification on bank profitability and risk By adopting an income diversification strategy, banks can effectively mitigate risks in operating activities Furthermore, a greater emphasis on non-interest activities can bolster bank profits Importantly, as banks engage in more extensive income diversification, they tend to encounter reduced levels of risk, ultimately leading to increased profitability Additionally, the research explores the influence of several other factors on bank risk, including the effects of the COVID-19 pandemic It is worth noting that the banking sector's profitability may decline while the associated risk may rise during epidemic periods due to measures such as social distancing, lockdowns, heightened unemployment, and business closures The research results are detailed as follows:
The lagged variable of profitability and risk have a positive impact on the business performance This result is similar to the study of Vinh & Mai (2015) with profitability, whereas, it has an opposite result of risk sector Therefore, it indicates that the operating results of the banks each year will depend on the operating results of the previous year, and moreover, if the banks operate business effectively, this result will be better and better
Regarding income diversification variable (HHI_REV), it has a positive relationship between income diversification and profitability (ROA and ROE), however, it has a negative impact on risk (ZScore) Besides, this result is strongly confirmed by the study of Vinh & Mai (2015) because of the same empirical results
With respect to a leverage ratio (L_A), it is a negative impact on both profitability model and ZScore model The result is strongly supported by some studies such as Chiorazzo et al (2008), Sanya & Wolfe (2011), and Vinh & Mai
(2015); however, with ZScore variable, it is contrary to Vinh & Mai (2015) Within bank resources, a bank cannot develop both of interest and non-credit activities at the same time Therefore, in order to increase income diversification, the bank should pay more attention to non-interest income generating activities, leading to reduce the number of loans
With a bank size (SIZE), this variable not only has a positive impact on profitability (ROA model and ROE model), but it also has a positive impact on risk
In addition, it is similar to the results of some studies such as K J Stiroh & Rumble (2006), Chiorazzo et al (2008), or Gurbuz et al (2013) As a result, the more expansion the bank size is, the more income the diversification brings to bank and the less risk the banks confront
With regard to an annual growth rate of total assets (ASSET_GRO), while it has a negative impact on ROA, this variable has an opposite impact on ROE model and Zscore, contributing to have a negative impact on risk In addition, ASSET_GRO variable is highly confirmed because of the same as some previous studies such as Lee et al (2014), or Vinh & Mai (2015), nevertheless, GL_GRO is opposite result of ZScore to Vinh & Mai (2015)
Regarding a gross loans growth rate, it is statistically significant with ROA model and ZScore, whereas it is insignificant impact on ROE variable According to Vinh & Mai (2015), these authors present that it is a negative relationship between Zscore and positive impact on income diversification However, Sanya & Wolfe (2011), K J Stiroh & Rumble (2006), Chiorazzo et al (2008), or Gurbuz et al (2013) have the same result with ROE variable about the statisticcal insignificance
About a covid turmoil variable, it is statistically significant and has a positive impact on both the profitability (ROA model and ROE model) and ZScore model In addition, it is similar to the results of some studies such as Le et al (2022) As a result, the emergence of the Covid-19 crisis may indeed have adverse implications for profitability Nevertheless, it also presents an opportunity for Vietnamese commercial banks to mitigate risks within their banking operations and initiate substantial restructuring efforts, all while implementing a more diversified approach
The empirical results of the topic have highly strengthened the theoretical bases in Chapter 2 and have contributed to the foundation of research related to income dversification in the future The study has differences from many previous studies such as research time with the latest data or adding more variables to evaluate impact of income diversification on profitability and risk As a result, according to some previous studies, accepting hypothesis 1 “The higher the degree of income diversification is, the higher the profitability of the bank gains” and rejecting hypothesis 2 “The higher value the income diversification gains, the higher the risk the bank confronts” are appreciate and logical.
Recommendations
According to the above result, the author will give some recommendations as follows:
Firstly, it is necessary for Vietnamese commercial banks to improve a credit quality to minimize risk, to have a right strategy, to improve the operating management as well as better liquidity risks management because good liquidity management is a mandatory requirement in banking operation However, during a period since the economy has affected seriously by the Covid-19 pandemic, the high credit ratio also means that banks could have to face a huge risk of bad debt Therefore, banks need to strengthen and actively shift the proportion of lending activities to non-interest income sources such as income from fees, foreign exchange trading or capital contribution, buying shares by steady and specific strategies such as building an appropriate proportion of non-interest income in accordance with a size and technology of each bank The integration with Fintech allows banks to develop new products and services, such as mobile payments, e-wallets, and personalized financial solutions This helps banks diversify their income streams and meet the increasing demands of customers, enhancing customer experience through fast, convenient, and secure services in the context of growing economic and technological trends It is essential for banks to seek to diversify the bank's portfolio of income-generating activities by exploring new business lines, products, and services; enhance technology services This can help reduce over-reliance on a single income source and enhance overall profitability while managing risk
Secondly, the Vietnamese commercial banks should develop a comprehensive strategic plan that incorporates income diversification as a key objective It is necessary to set clear targets and timelines for diversifying income sources, while considering the potential impact on profitability and risk Additionally, banks should integrate Fintech because it brings advanced technologies like Blockchain and big data, which help banks improve operational efficiency, optimize processes, and provide more modern services Furthermore, Fintech helps banks implement effective performance measurement metrics to evaluate the profitability, risk implications of income diversification including regular monitoring of key financial indicators, such as return on assets, return on equity, non-performing loan ratios, and capital adequacy ratios
Thirdly, the commercial banks should establish a robust risk management framework including risk identification, assessment, mitigation accounting for the risks associated with income diversification Vietnamese commercial banks need to build a quality of human resource system, a professional training system, encourage cross-functional knowledge sharing, and attract professionals with experience in diverse areas of banking operations Moreover, income diversification often involves adopting new technologies and deploying more complex products and services Bank employees need high technological skills to effectively use digital systems, manage data, analyze customer information, and consequently provide better advisory and relationship management services Additionally, employees are reliable sources for identifying and assessing risks, enabling banks to proactively manage these risks
Last but not the least, the banks should ensure compliance with relevant regulations and guidelines while pursuing income diversification This ensures that income diversification activities are conducted within the legal and regulatory framework and help to maintain the stability and integrity of the banking system while safeguarding the interests of stakeholders Besides, by emphasizing compliance with regulations and establishing effective governance structures, the commercial banks could oversee and manage income diversification activities, ensuring alignment with the bank's risk appetite and strategic objectives.
Limitations and future research directions
Because the author has limitation about time, facilities as well as collected data sources, the study has the sample data is slightly small including only 30 Vietnamese commercial banks with an observation over period of 11 years from
2012 to 2022 In addition, the study has not taken into account foreign commercial banks in Vietnam Hence, it is not objective to evaluate the Vietnamese commercial banking system In addition, factors analyzing income diversification impacting on profitability and risk are some of the typical factors of banks Meanwhile, the study has not considered some factors such as inflation, GDP, or credit risk in the model This is because the study mainly considers some factors reflecting income diversification affecting profitability and risk in most economies Consequently, based on the limitations mentioned, the author suggests some future studies:
• Future studies can increase more the number of observations through increasing the number of years of observations, the number of observations, or both of them Since the scope of data source is larger, it is more highly accurate, and it is possible to assess more fully the impact of income diversification on profitability and risk
• Future studies can expand more model by adding some variables such as inflation, GDP, or credit risk Moreover, supplementing a marginal efficiency is one of potential solutions to complete the measure of income diversification
At that time, the topic will evaluate more comprehensively the impact of income diversification on profitability and risk.
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List of Vietnamese commercial banks
Vietnam Bank for Agriculture and Rural Development AGR
Vietnam Joint Stock Commercial Bank of Industry and Trade CTG
Joint Stock Commercial Bank for Investment and
Joint Stock Commercial Bank for Foreign Trade of
Asia Commercial Joint Stock Bank ACB
An Binh Commercial Joint Stock Bank ABB
Bao Viet Joint Stock commercial Bank BVB
Viet Capital Commercial Joint Stock Bank VCA
Bac A Commercial Joint Stock Bank BAB
LienViet Commercial Joint Stock Bank (Lienviet Post
Vietnam Public Joint Stock Commercial Bank OTC Southeast Asia Commercial Joint Stock Bank
The Maritime Commercial Joint Stock Bank MSB Kien Long Commercial Joint Stock Bank KLB Viet Nam Technological and Commercial Joint Stock
Nam A Commercial Joint Stock Bank NAB
Orient Commercial Joint Stock Bank OCB
Military Commercial Joint Stock Bank MBB
Vietnam International Commercial Joint Stock Bank VIB
Saigon Bank for Industry & Trade SGB
Saigon-Hanoi Commercial Joint Stock Bank SHB Saigon Thuong Tin Commercial Joint Stock Bank STB TienPhong Commercial Joint Stock Bank TPB
Viet A Commercial Joint Stock Bank VAB
Vietnam Commercial Joint Stock Bank for Private
Petrolimex Group Commercial Joint Stock Bank
Viet nam Export Import Commercial Joint Stock
Ho Chi Minh city Development Joint Stock
Variables: fitted values of ROA
Breusch-Pagan / Cook-Weisberg test for heteroskedasticity
Prob > F = 0.0000 F( 1, 28) = 69.700 H0: no first-order autocorrelation Wooldridge test for autocorrelation in panel data
Wu-Hausman F(1,286) = 11.0112 (p = 0.0010) Durbin (score) chi2(1) = 10.7513 (p = 0.0010) Ho: variables are exogenous
Variables: fitted values of ROE
Breusch-Pagan / Cook-Weisberg test for heteroskedasticity
Prob > F = 0.0000 F( 1, 28) = 91.888 H0: no first-order autocorrelation Wooldridge test for autocorrelation in panel data
Wu-Hausman F(1,286) = 6.79629 (p = 0.0096) Durbin (score) chi2(1) = 6.73138 (p = 0.0095) Ho: variables are exogenous
Variables: fitted values of ZScore
Breusch-Pagan / Cook-Weisberg test for heteroskedasticity
Prob > F = 0.0000 F( 1, 28) = 42.812 H0: no first-order autocorrelation Wooldridge test for autocorrelation in panel data
Wu-Hausman F(1,286) = 6.86489 (p = 0.0093) Durbin (score) chi2(1) = 6.79773 (p = 0.0091) Ho: variables are exogenous