Overall, this study has found that total assets, cash size, return on assets and population have positive effects on banking income diversification while gross domestic product and infla
INTRODUCTTION .- 5< 55S+cS+rrtEEEitEErirEEEiiiriiiirriiiirirrrrrirrrrii 1
Commercial banks serve as essential financial institutions where individuals can securely deposit their money They engage in key activities such as accepting deposits, providing loans, and facilitating payments, creating mutual benefits for both the bank and its customers through increased asset value The operations of commercial banks play a crucial role in fostering stable economic development, which is vital for the prosperity of any nation.
As economic development, advanced technology, and competitive markets evolve, commercial banks are shifting their focus from traditional interest income to non-traditional banking activities that enhance income diversification This trend allows banks to operate in various sectors, improving their competitiveness and generating alternative revenue streams The advantages of income diversification became particularly evident during the Covid-19 pandemic (2019-2022), when traditional banking activities faced significant disruptions due to social distancing measures By pivoting to non-traditional banking operations, many commercial banks worldwide not only stabilized their overall returns but also maintained robust banking operations during challenging times.
In Vietnam, the trend of income diversification in commercial banks has emerged over the years, driven by market integration and heightened competition Research by Le et al (2022) indicates that while the proportion of non-interest income in the total income of commercial banks is on the rise, the growth rate remains slow and has yet to meet the targets outlined in the Vietnam Banking Development Strategy.
To address challenges in banking income diversification, it is essential to identify the factors influencing this diversification in commercial banks Research indicates that the level of income diversification varies among banks due to various macroeconomic and internal factors.
Nghiên cứu của Le và cộng sự (2022) tập trung vào việc đa dạng hóa thu nhập và rủi ro nợ ngân hàng tại Việt Nam, đặc biệt trong bối cảnh COVID-19 Bài viết phân tích các yếu tố ảnh hưởng đến sự ổn định tài chính của ngân hàng trong giai đoạn khủng hoảng, nhấn mạnh tầm quan trọng của việc quản lý rủi ro và chiến lược thu nhập đa dạng Kết quả nghiên cứu cung cấp cái nhìn sâu sắc về tình hình tài chính ngân hàng và những thách thức mà ngành này phải đối mặt trong thời kỳ dịch bệnh.
Recognizing the significance of income diversification in the banking sector, this study explores the factors influencing income diversification among Vietnamese commercial banks The research aims to identify the impacts of various elements on the income diversification strategies of these banks, providing empirical evidence from Vietnam.
This study aims to assess the impact of various macroeconomic and internal banking factors on the income diversification of Vietnamese commercial banks To achieve this, the author gathers secondary data from reliable online sources, including news articles, reports, research studies, and financial statements of these banks The research employs a regression model, utilizing a processed database of observational samples from 27 Vietnamese commercial banks spanning from 2007 to 2021, to elucidate the relationship between the key research factors and income diversification in the sector.
This study is organized into five main chapters: the first chapter introduces the topics to be discussed, the second chapter provides the theoretical framework and literature review, the third chapter outlines the data and methodology used in the research, the fourth chapter discusses the study results, and the final chapter presents a comprehensive conclusion along with suggestions for further solutions.
LITERATURE REVIEW .-., H rà 3 2.1 Income structure of commercial bannKS -. -csss+crcxerrerxerrrrrrrrrtrirrrrrrrrrrrrrrrrrrrrrrrrii 3 2.2 (v9001:19)0\42v3)001x55 1101177 6 2.2.1 Definition of bank income diversification 2.2.2 Income diversification and bank financial performance essences 4 2.3 Bank income diversification - a review of relevant literature .- - s 5
2.1 Income structure of commercial banks
A commercial bank serves as a vital financial institution, primarily functioning as a credit intermediary, payment facilitator, and money generator Its core activities include accepting deposits, offering loans and credit, managing payment accounts for customers, and providing safekeeping and remittance services Additionally, commercial banks may participate in various other income-generating activities to enhance their profitability.
Commercial banks generate income through various services and operations, which can be quantified in monetary terms This income consists of two primary components: interest income and non-interest income Profit, a key aspect of this income, is calculated by subtracting costs and expenses from the total income generated by the bank's activities.
Interest income serves as the primary revenue source for commercial banks, typically constituting over 50% of their net operating income This income is derived from the bank's core credit activities, which are fundamental to traditional banking Acting as credit intermediaries, commercial banks accept deposits from individuals with surplus funds and offer loans to those in need By accepting deposits at a lower borrowing rate and issuing loans at a higher lending rate, banks generate profit from the interest rate spread, known as interest income.
Non-interest income, derived from non-credit related or non-traditional banking activities, constitutes over 40% of the operating income for commercial banks in the United States, as noted by DeYoung and Rice (2004) Research and surveys indicate that in developed financial markets, non-interest income typically represents a significant portion of total operating income.
Non-interest income for a commercial bank includes several key components: net gains from service charges and fees, which encompass transaction fees and monthly account maintenance charges, as well as fees for online and SMS banking services Additionally, it comprises net gains from gold and foreign currency trading, as well as trading securities and investment securities, including corporate and government bonds Furthermore, this income category also covers gains from other activities such as diverse investments, collaborations, and cross-selling of various products.
2.2.1 Definition of bank income diversification
Bank income diversification, as defined by Zhou (2014), refers to the balance between interest income and non-interest income, with a focus on the latter to assess diversification levels Commercial banks enhance their income diversification by expanding their sources of non-interest income or by increasing the share of non-interest income within their overall operating income.
According to Gurbuz et al (2013), complete income diversification for banks occurs when interest income and non-interest income each constitute 50% of the bank's net total income While interest income typically serves as the primary revenue source for commercial banks, it is generally expected to account for at least half of the net total income.
According to Andrzejuk (2017), effective income diversification for banks requires a balanced approach that includes both interest and non-interest income, as this strategy enhances profitability and operational efficiency.
Income diversification in banking refers to a bank's expansion into non-traditional activities, leading to a higher ratio of non-interest income to total operating income This strategy aims to enhance revenue streams while maintaining the bank's reputation and ensuring the quality of traditional banking services remains intact.
2.2.2 Income diversification and bank financial performance
Income diversification affects banking performance in many ways, of which the most noticeable are:
Engaging in diverse activities significantly boosts profit opportunities for commercial banks by allowing them to reach a wider customer base, strengthen partnerships, and increase revenue potential Research by Sanya and Wolfe (2011) indicates that diversification is key to enhancing both profitability and operational stability for these financial institutions.
Increasing income diversification significantly lowers the bankruptcy risk for commercial banks, as evidenced by Nguyen and Hoang (2019) By generating additional non-interest income through investments and various activities, banks reduce their dependence on traditional interest income This strategy allows banks to maintain a reserve of assets, providing a safeguard against potential deficits in customer deposits.
To enhance their competitive edge, commercial banks are diversifying their income streams, which also exposes them to greater competitive pressures in emerging sectors, as noted by Tam et al (2022) referencing Winton (1999).
Increased involvement in diverse sectors heightens a bank's exposure to risks, as external factors can negatively impact profitability Banks must carefully balance expected returns with associated risks when pursuing non-interest income activities According to Trinh et al (2018), while diversifying income can enhance profits, it also escalates risk levels, particularly for State-owned commercial banks, highlighting the need for effective risk management in non-traditional banking ventures.
Engaging in non-traditional banking sectors allows commercial banks to diversify their income, presenting both opportunities and risks This strategic move enhances their competitive edge and fosters development within the industry.
2.3 Bank income diversification - a review of relevant literature
Rogers and Sinkey Jr (1999) analyze the characteristics of U.S commercial banks involved in non-traditional banking from 1989 to 1993 Their findings reveal that these banks are generally larger, possess lower net interest margins and core deposits, and demonstrate reduced risk Additionally, larger banks with fewer core deposits, facing competitive interest rates that limit traditional banking activities, tend to generate more diverse revenue streams from non-traditional banking sectors.
Shahimi et al (2006) investigate the involvement of Malaysian Islamic commercial banking in various fee income or non-traditional banking activities during the years from
1994 to 2004 The results show that higher levels of fee income generating activities usually associate with higher levels of banking assets and deposits, along with less risks.
DATA AND METHODOLOGY 0.cessssssssssssssssstssssssseesssneeessutecessneeceesueeeesnseeesssseeseenssess 10 3.1 Research model specifications 0 eessssessssssssssessssescssseescsseesesssesessseesssnseecssneeeessuessssseesssnneessanes 10 3.2 Measure bank income diversification csesssssccsssescssesscseecsssecsessteeessntecessseessssseeessseesssneesssases 10 3.3 Other Control Variables .ssssessssssesssssessssssessssseesssseessssseesssseeesssseeesssseeesssseessssseessssseesssneetssseessaneessasss 11 3.3.1 a4 7 <
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Table 4.1: Summary statistics Variables | Obs Min Max Mean Std P25% | P50% | P75%
Source: Statistical results performed by Stata 17.
Table 4.1 presents the statistical analysis conducted using Stata 17, detailing key metrics for all variables, including the number of observations (Obs), minimum (Min) and maximum (Max) values, mean (Mean), standard deviation (Std), and the 25th (P25%), 50th (P50%), and 75th (P75%) percentiles.
From the summary statistics table, we can see that the DIV index value ranges from
The income diversification level index (DIV) for Vietnamese commercial banks ranges from 0 to approximately 0.5, indicating a normal value range The average DIV from 2007 to 2021 is 0.28, reflecting an average income diversification level of 28% The median DIV value of 2.888 suggests that half of the observations fall below this figure, with 25% below 0.193 and the top 25% ranging from 0.388 to the maximum Notably, the Vietnam Maritime Commercial Joint Stock Bank (MSB) recorded the highest DIV value of approximately 0.499 in 2014 and 2017 Additionally, there were 22 instances of the minimum DIV value of 0.000 across about 11 banks between 2010 and 2021.
The LNTA value, which reflects the logarithmic volume of total assets and indicates bank size, ranges from 5.626 to 7.886, with an average of 6.712 Larger banks typically exhibit higher LNTA values, suggesting a positive correlation between bank size and asset volume.
STUDY RESULTS AND DISCUSSION 55c< Series 18 4.1 DESCTIPTIVE StatẽSECS HH Hee 18 4.2 Correlation Matrix ceccsssescsssesscssessssssesscsseessssssssssseesssseesssstessssseeesssseecsssseesssnseesssnessensteessssteesssneesssnseess 20 4.3 Main results hố 21 4.4 General discussion and practical CXAMPIES . -ô-cxxeexxerrrrtrrrtrrirkrrirrrrrrrrrrree 26 CHAPTER 5: CONCLUSION 555-5222 HH HH rh 31 REFERENCES -SSSH HH HH HH HH HH HH HH He 33
Table 4.1: Summary statistics Variables | Obs Min Max Mean Std P25% | P50% | P75%
Source: Statistical results performed by Stata 17.
Table 4.1 presents a comprehensive summary of the statistical results generated by Stata 17, detailing key metrics for all variables This includes the total number of observations (Obs), as well as the minimum (Min) and maximum (Max) values Additionally, the table provides the mean value (Mean), standard deviation (Std), and the 25th (P25%), 50th (P50%), and 75th percentiles (P75%) for each variable, offering a thorough overview of the dataset's distribution and central tendencies.
From the summary statistics table, we can see that the DIV index value ranges from
The income diversification level index (DIV) of Vietnamese commercial banks ranges from 0 to approximately 0.5, indicating a normal value range The average DIV from 2007 to 2021 is 0.28, reflecting an income diversification level of about 28% The median DIV is 2.888, suggesting that half of the observations fall below this value, while the other half exceeds it Approximately 25% of observations are below 0.193, and the top 25% range from 0.388 to the maximum value Notably, the highest DIV of around 0.499 was recorded by the Vietnam Maritime Commercial Joint Stock Bank (MSB) in 2014 and 2017 Additionally, there were 22 instances of a minimum DIV value of 0.000 across approximately 11 banks between 2010 and 2021.
The LNTA value, which reflects the logarithmic volume of total assets and signifies bank size, ranges from 5.626 to 7.886, with an average of 6.712 Analysis of the database shows that larger banks consistently exhibit higher LNTA values.
Vietnamese banks have experienced an annual growth rate of 18%, indicating significant expansion over the years In 2021, the Joint Stock Commercial Bank for Investment and Development of Vietnam (BIDV) recorded the highest LNTA value of 7.886, solidifying its position as one of the largest state-owned commercial banks in the country The deposit ratios of these banks varied, with a minimum value of 0.226 and a maximum of 0.893, resulting in an average deposit-to-total-assets ratio of approximately 63.8% from 2007 to 2021.
On average, equity constitutes 9.1% of the total assets of banks in Vietnam, with Lien Viet Post Joint Stock Commercial Bank (LienVietBank) reporting the highest equity ratio at 46.2% in 2008, a figure influenced by its newly established status Cash and cash equivalents represent 19.1% of total assets for Vietnamese banks from 2007 to 2021 The mean Return on Assets (ROA) of 0.008 indicates that these banks generate an average of 8% income per unit of assets during this period, although some banks experienced negative ROA due to losses Macroeconomic indicators, such as LNGDP and LNPOP, show consistent growth in Vietnam's GDP and population from 2007 to 2021 The Consumer Price Index (CPI) reflects an average annual increase of 6.5%, with the highest inflation rate of 19.9% recorded in 2008 and the lowest at 0.6% in 2015.
Source: Pairwise test results performed by Stata 17.
Table 4.2 displays the results of the correlation test for nine variables, utilizing the Pairwise test method The upper numbers in the value cells indicate the correlation coefficients, while the values in parentheses represent the corresponding significance levels Coefficients marked with an asterisk (*) signify statistical significance at the 5% level.
The analysis reveals significant positive correlations between DIV and both LNTA and ROA, with coefficients of 0.145 and 0.237, respectively Furthermore, LNTA shows strong positive correlations with DEPOSIT, LNGDP, and LNPOP, while exhibiting negative correlations with EQUITY, CASH, and CPI Given that deposits are typically the largest component of total assets, their size is positively linked to total assets, which tend to grow alongside GDP and population DEPOSIT is also positively correlated with LNGDP and LNPOP, but negatively with EQUITY, CASH, ROA, and CPI Additionally, EQUITY has positive correlations with CASH, ROA, and CPI, but negative correlations with LNGDP and LNPOP CASH shares positive correlations with ROA and CPI, while being negatively correlated with LNGDP and LNPOP Lastly, ROA is positively correlated with CPI and negatively correlated with both LNGDP and LNPOP.
The macroeconomic variables LNGDP, CPI, and LNPOP exhibit strong correlations, with the highest positive correlation of 0.970 between LNGDP and LNPOP In contrast, LNGDP shows a negative correlation of 0.730 with CPI, while CPI and LNPOP are also negatively correlated at 0.750 These interrelationships among the independent variables may lead to multicollinearity issues in the OLS model.
Step 1: Perform an OLS regression model
Table 4.3: OLS regression model results
Source: OLS regression results performed by Stata 17.
Note: Table 4.3 presents the OLS regression results of the correlations between 8 independent variables and DIV, the coefficients are shown in DIV column with ***, **, *
21 denotes the significance at 1%, 5%, 10% level respectively; the values in ( ) indicate the Robust standard errors.
The findings indicate that DIV exhibits significant positive correlations with LNTA, ROA, and LNPOP, while showing a notable negative correlation with LNGDP However, the Variance Inflation Factors (VIF) test reveals a concerning average VIF of 6.59, surpassing the acceptable threshold of 5, indicating high multicollinearity within the regression model To address this issue, the author recommends removing the LNPOP variable from the OLS model due to its strong correlation with other macroeconomic variables, specifically LNGDP and CPI, as discussed in Part 4.2 of the correlation matrix, and to proceed with a revised OLS model in Step 2.
Step 2: Fix multicollinearity for OLS regression model
Table 4.4: Fixed OLS regression model results
Source: OLS regression results performed by Stata 17.
Note: Table 4.4 presents the fixed OLS regression results of the correlations between 7 independent variables (except for LNPOP) and DIV, the coefficients are shown
In the DIV column, significance levels are indicated by ***, **, and *, corresponding to 1%, 5%, and 10% respectively, with robust standard errors shown in parentheses The final column presents the Variance Inflation Factor (VIF) test results for all independent variables Following the removal of one macroeconomic variable, the VIF values for seven independent variables, along with the mean VIF, all fall below the acceptable threshold of 5.
The findings indicate a significant positive correlation between LNTA and DIV at a 5% significance level, with a coefficient of 0.047 suggesting that for every unit increase in LNTA, DIV increases by 0.047 units This demonstrates that total assets positively influence income diversification among commercial banks in Vietnam, highlighting that larger banks benefit from enhanced opportunities for income diversification This conclusion aligns with previous research conducted by Hahm (2008), Andrzejuk (2017), Tram and Nguyen (2018), and other studies.
A significant positive correlation exists between cash size and bank income diversification, with a 0.166 unit increase in diversification for each percentage increase in cash, at a 10% significance level Research by Suryanto et al (2021) indicates an inconsistent relationship between bank liquidity assets and non-interest income, which can vary positively or negatively Cash size, representing cash and cash equivalents to total assets, serves as a key indicator of effective bank liquidity management Banks with strong liquidity management are better positioned to maintain stable operations, mitigate liquidity risks, and pursue income diversification Consequently, cash size positively influences Vietnamese commercial banks from 2007 to 2021, despite the correlation's relatively low significance level of 10%.
A significant positive correlation exists between Return on Assets (ROA) and income diversification (DIV) at the 1% level, indicating that for every percentage increase in ROA, DIV rises by 3.793 units This suggests that ROA plays a crucial role in the income diversification of Vietnamese commercial banks Banks with higher ROA demonstrate efficient operations and effective income management, leading to increased profits through proactive income diversification A higher ROA signifies greater income generation from assets, reflecting the bank's ability to derive revenue from multiple sources, thereby reinforcing the positive relationship between ROA and banking income diversification, as supported by previous studies (Andrzejuk, 2017; Phan et al., 2022).
A significant negative correlation exists between LNGDP and DIV at a 5% significance level, indicating that for each unit increase in LNGDP, DIV decreases by 0.139 units This suggests that the rapid economic growth in Vietnam from 2007 to 2021 has hindered income diversification among commercial banks The competitive landscape created by this growth requires banks to adapt quickly, while effective income diversification typically necessitates a stable economic environment These findings align with previous research by Hahm (2008), Louzis and Vouldis (2015), and Doan (2019).
The Consumer Price Index (CPI) exhibits a significant negative correlation with income diversification (DIV) at a 5% significance level, indicating that a 1% increase in CPI results in a decrease of 0.447 units in DIV This relationship highlights that rising inflation adversely affects the income diversification of Vietnamese commercial banks from 2007 to 2021 High inflation rates can negatively impact the operations and profitability of various industries, including banking, thereby restricting banks' ability to expand operations and diversify their income streams, aligning with findings from previous studies (Hahm, 2008; Hakimi et al., 2012; Louzis and Vouldis, 2015; Doan, 2019).