GRADUATION THESIS FINTECH AND INCOME DIVERSIFICATION: IMPACTS ON PROFITABILITY AND RISKS OF VIETNAMESE COMMERCIAL BANKS MAJOR: FINANCE - BANKING CODE : 7340201 NGUYEN THANH HANG HO
INTRODUCTION
RATIONALE OF THE STUDY
Over the past decades, the banking industry has undergone remarkable transformation and development in both scale and quantity Banking activities increasingly participate in more sectors in the economies One of the leading causes of this achievement is the rapid progress of information and communications technology in general, or financial technology in particular The financial market is also filled with tools such as: online savings, commercial documents, derivative finance, e-wallets, smart banking, which attract customers to transact more electronically through smart devices, instead of going to bank headquarters or branches (Tram Thi Xuan Huong and Nguyen Tu Nhu 2020)
Banks, as the core of the financial system, are continuously innovating their service delivery, driven by advances in communication technology enabling cross-border financial activities Additionally, developments in information technology facilitate the construction of robust credit systems, enhancing banking operations (Lee et al., 2021) Since the 21st century, global banks have diversified their activities to adapt to market pressures and pursue higher profits, as noted by DeYoung and Roland (2001) Between 2013 and 2021, banks experienced an increase in bad debts, prompting the Vietnamese Government and State Bank of Vietnam (SBV) to implement restructuring policies, including Decision No 689/QD-TTg dated June 8, 2022, aimed at stabilizing and strengthening the banking sector.
Between 2021 and 2025, restructuring the credit institution system associated with bad debt settlement aims to limit bad debts and minimize the adverse impact of credit activities on commercial bank performance To enhance business efficiency and mitigate the effects of credit operations, one key strategy is income diversification, allowing banks to broaden revenue sources and strengthen financial stability These reforms are essential for creating a more resilient banking sector capable of managing credit risks effectively.
In a competitive banking environment, diversification of income sources has become essential for financial stability and sustained profitability, especially in developing countries where operational efficiency and marketing strategies may be less advanced (Hunjra et al., 2020) Over the past two decades, banks have increasingly expanded their revenue streams beyond traditional interest income to include non-interest income from financial services like transfer fees, credit offerings, and e-banking (Asif and Akhter, 2019; Syahyunan et al., 2017) Income diversification plays a crucial role in risk management and stabilizing financial operations, reducing overreliance on interest-based revenue while enhancing resilience against rising credit risks (Zhou, 2014) Technological innovations, particularly fintech, have further boosted non-interest income, offering benefits such as risk minimization and competitive advantage amid global economic integration (Arner, Barberis, and Buckley, 2016) Regulatory initiatives like Vietnam’s Decision No 2655/2019/QĐ-NHNN and Decree No 80/2016/NĐ-CP have significantly shaped the fintech landscape, facilitating electronic payments and e-wallet services that drive growth and innovation in the banking sector (Tran Thi Hai Yen).
The future of Fintech in Vietnam is set for significant transformation driven by ongoing technological advancements, including the adoption of Banking 3.0, Artificial Intelligence, Big Data, and Analytics, which will reshape both fintech companies and traditional banks Since 2015, awareness and adoption of FinTech services have steadily increased globally, reaching 64%, with countries like China and India leading at 87% In 2023, most basic banking operations are expected to be fully digitized at commercial banks, achieving a favorable cost-to-income ratio of 30-40%, while banks such as TPBank, VIB, MB, and VPBank have already surpassed 90% transaction rates via digital channels Many banks are actively partnering with Fintech firms to expand services, leveraging technological innovations to improve customer experiences, streamline operations, and foster innovative product offerings.
One of the primary challenges for banks is the urgent need to invest in advanced technology and streamline their operational models Outdated systems and processes currently burden many banks, hindering efficiency and driving up operating costs To stay competitive against agile fintech companies, banks must adopt innovative technologies to enhance their service offerings and deliver a superior customer experience.
To stay competitive amid rapid Fintech growth, commercial banks must prioritize continuous technological innovation as a long-term strategic goal However, resource constraints often cause banks to lag behind, risking market share loss Fintech also introduces significant challenges in cybersecurity and data protection, emphasizing the need for robust digital security measures Additionally, a shortage of tech-savvy, multilingual talent—particularly in Vietnam—impedes digital transformation efforts Therefore, embracing technological advancement is crucial for banks to navigate evolving digital financial landscapes successfully (Dao My Hang and Le Thi Dieu Linh, 2024).
Fintech is revolutionizing the banking industry by transforming access to financial technology and challenging traditional business models This shift impacts human resources, operational costs, and development strategies across individual banks and the entire sector As technology advances, banks must address new challenges related to efficiency, operational risks, and long-term sustainability, prompting ongoing research into Fintech’s future implications for banking stability and performance.
This study explores the impact of Fintech development and information technology on income diversification and risk management in Vietnamese commercial banks, addressing existing research gaps Building on previous work by Tram Thi Xuan Huong and Nguyen Tu Nhu from Ho Chi Minh City University of Economics, it specifically examines how the Vietnam ICT Index influences business diversification Focusing on the period from 2012 to 2023, the research delves into how Fintech adoption and income diversification affect bank profitability and risk levels Recognizing the complexity of these issues, the study aims to offer valuable insights into effective income diversification strategies and Fintech applications to promote sustainable growth and enhanced risk management for Vietnamese banks.
RESEARCH OBJECTIVE
This study aims to analyze the impact of income diversification and Fintech adoption on the profitability and risk profile of Vietnamese commercial banks between 2012 and 2023 By examining these factors, the research provides valuable insights into how technological innovation and diversified revenue streams influence bank performance The findings will help identify key strategies to enhance profitability while managing associated risks Based on the analysis, the study offers targeted recommendations for Vietnamese commercial banks to improve their business performance and remain competitive in a rapidly evolving financial landscape.
Firstly, analyzing the impact of the application of Fintech and income diversification on the profitability and risks of Vietnamese commercial banks over the period of 2012 to 2023
After assessing the level of influence, the study offers strategic recommendations to enhance profitability and reduce risks for Vietnamese commercial banks These include diversifying income sources and implementing advanced financial technologies, aiming to strengthen the banks' financial stability and competitiveness in the near future.
RESEARCH QUESTIONS
From the Research Objectives as presented above, the author quoted two specific research questions:
- Research question 1: How does Fintech and income diversification affect the profitability and risks of Vietnamese commercial banks over the period of 2012 to 2023?
- Research question 2: What recommendations can help improve the profitability and minimize risk as diversifying income and applying financial technology for Vietnamese commercial banks?
RESEARCH SCOPE
This thesis investigates the impact of financial technology and income diversification on the profitability and risk management of Vietnamese commercial banks Focusing on 27 listed joint-stock banks, the study analyzes data from 2012 to 2023—a crucial period marked by significant debt restructuring reforms in Vietnam's banking sector The research highlights how technological advancements and diversified income sources influence bank performance and stability amidst industry-wide reforms.
RESEARCH METHOD
To achieve the research objectives, the thesis employs a mixed-methods approach, combining both qualitative and quantitative techniques
In this study, qualitative methods such as synthesis, statistical analysis, description, comparison, and data analysis are employed to develop a comprehensive theoretical framework on income diversification and its effects on profitability and bankruptcy risk in Vietnamese commercial banks Additionally, reviewing and synthesizing prior research from both Vietnam and international contexts provides a solid foundation for creating a research model and formulating relevant hypotheses.
The study employed quantitative research methods, utilizing data from reputable sources such as the Fiinpro system provided by Ho Chi Minh University of Banking, the Vietnam ICT Annual Report (2012-2022), and the World Bank for macroeconomic indicators like inflation and economic growth Data analysis was conducted using Stata 17.0, starting with descriptive statistics and correlation coefficient analysis The study included multicollinearity testing with VIF, as well as Hausman tests to identify model issues related to variance and autocorrelation To ensure the accuracy of results and address potential endogeneity, the research applied the Generalized Method of Moments (GMM) estimation technique developed by Arellano and Bover (1995) and Blundell and Bond (1998).
SIGNIFICANCE OF THE RESEARCH
This study advances the understanding of factors influencing the profitability and risk of Vietnamese commercial banks, building on previous research to solidify existing models and scales Additionally, it contributes to the broader body of knowledge on financial technology and income diversification in the banking sector The identified advantages and limitations of the research provide valuable insights and serve as a foundation for future in-depth studies in this field.
In terms of practice, the study identifies factors affecting the profitability and risk of 27 Vietnamese Commercial Banks and the level of impact of those factors.
RESEARCH STRUCTURE
This study included a total of five chapters as follow:
Chapter 1 INTRODUCTION: Chapter 1 will present the reasons for choosing the topic, thereby determining the research objectives from general to specific, then giving appropriate research questions, clearly defining the scope and objects of the research Besides that, the author also presents the research method, the contribution of the topic and finally the structure of the topic
Chapter 2 LITERATURE REVIEW: Chapter 2 includes an overview theories, presents the basic theory on the impact of income diversification on the operational efficiency of commercial banks At the same time, it summarizes some previous relevant empirical studies in Vietnam and abroad to identify research gaps and build a foundation for the research model in the next chapter
Chapter 3 RESEARCH MODEL AND DATA: Chapter 3 establishes a research model based on the proposed basis for model selection Then it will explain the variables selected in the model, develop methods, research procedures, data processing tools, and data analysis techniques used in the research process
Chapter 4 RESEARCH RESULTS: This chapter presents and interprets the results of quantitative research through analysis and processing of collected data through STATA17.0 software, including parts such as descriptive statistics, correlation matrix, regression and selection of optimal models through testing From there, it provides an explanation of the impact of independent variables on dependent variables
Chapter 5 CONCLUSION AND RECOMMENDATIONS: Based on the results obtained in Chapter 4, comments and conclusions are made on the direction and level of impact of income diversification and Fintech on the operational efficiency of commercial banks in Vietnam From there, some recommendations are made to contribute to improving the operational efficiency of banks Finally, the author also points out some limitations of the thesis, and proposes further research directions to further improve the research related to the topic
In Chapter 1, the author explains the rationale for selecting the study focused on the impact of income diversification and Fintech on Vietnamese commercial banks' performance from 2012 to 2023 The chapter outlines the research objectives, scope, and methodology used to address key research questions, providing a clear framework for analyzing how technological advancements and diversified revenue streams influence bank efficiency and competitiveness in Vietnam's financial sector.
Building on Chapter 1, Chapter 2 delves into the theoretical foundations of the topic and reviews relevant empirical studies from both domestic and international sources This chapter synthesizes key theoretical concepts and summarizes empirical research to establish a solid basis for analysis and evaluation It aims to clarify the relationship between income diversification, Fintech integration, and the performance of Vietnamese commercial banks, thereby contributing to a deeper understanding of how technological and financial strategies impact bank performance.
LITERATURE REVIEW
THEORETICAL FOUNDATION
Modern Portfolio Theory (MPT), originating from Harry Markowitz's groundbreaking portfolio selection theory introduced in 1952, is a fundamental investment framework focused on optimizing asset allocation William Sharpe further advanced MPT with his development of the Capital Asset Pricing Model (CAPM) in 1964, which explains asset price formation and helps investors determine expected returns Central to MPT is the concept of constructing diversified portfolios that aim to maximize expected returns while minimizing investment risk, providing a scientifically grounded approach to efficient portfolio management (Fabozzi, Gupta, and Markowitz, 2002).
Modern Portfolio Theory (MPT) aims to create a diversified portfolio that balances risk and high returns by selecting assets with low correlation Diversification reduces overall investment risk because the impact of individual asset risks diminishes within the broader portfolio A key insight from Markowitz’s work is that an investor should focus on how each security's covariance with other assets affects the total portfolio variance, rather than just its own risk or expected return Therefore, evaluating securities in isolation is insufficient; instead, their contribution to the portfolio’s overall risk and return must be considered collectively.
This theory also established the "Efficient Frontier" method It represents the best combination of securities (those producing the maximum expected return for a given risk level) within an investment portfolio, usually depicted in graphic form as a curve on a graph comparing risk against the expected return The optimal portfolios plotted along this curve represent the highest expected return on investment possible, for the given amount of risk (Mangram 2013) Portfolios lying on the ―Efficient Frontier‖ represent the best possible combination of expected return and investment risk
Applying Modern Portfolio Theory to income diversification reveals that banks strategically implement this approach to reduce risks and enhance operational efficiency Diversification is particularly effective when income streams are independent and not positively correlated during periods of risk, leading to increased profitability and risk mitigation The portfolio balance model emphasizes that optimal asset allocation depends on factors such as expected returns, associated risks of financial assets, and the overall portfolio size, with management playing a key role in determining the ideal composition Furthermore, a bank's ability to maximize returns hinges on selecting appropriate assets and liabilities while managing the costs associated with acquiring and maintaining these assets (Atemnkeng and Nzongang, 2006).
Banks diversify their revenue streams to mitigate risk and improve operational efficiency When income sources are independent and not positively correlated during times of risk, diversification effectively boosts profits and minimizes vulnerabilities However, if revenue sources are highly correlated, diversification may not provide the anticipated risk reduction or profit enhancements.
The theory of financial intermediation by Diamond (1984) highlights that banks have a distinct advantage as financial intermediaries by efficiently connecting capital suppliers and demanders Their expertise allows them to address challenges such as information asymmetry, agency costs, and credit scale limitations, making them essential players in the financial industry.
2020) By addressing these market inefficiencies, banks play a crucial role in enhancing financial stability and efficiency
Goldsmith (1969) and Levine (1997) emphasize the crucial link between financial system development and economic growth, highlighting that efficient capital allocation drives economic progress Modern financial intermediation theories focus on key factors like information asymmetry, transaction costs, and regulatory frameworks, which underscore the vital role of institutions such as banks and insurance companies These financial intermediaries monitor borrowers, reduce bankruptcy costs, and diversify risks, thereby enhancing risk management and resource allocation As a result, they can sustain high financial leverage while maintaining relatively low risk levels, contributing significantly to overall economic stability and growth.
Diamond’s (1984) theory indicates that as banks issue loans to more businesses with independently profitable projects, the issue of information asymmetry decreases significantly This improvement allows banks to better assess creditworthiness, enhance monitoring, and reduce intermediation and agency costs As a result, banks are motivated to diversify their lending portfolios by providing credit to a wide range of unrelated businesses, which helps minimize overall risk.
Empirical studies reinforce the advantages banks derive from their financial intermediation activities, such as interest income from lending, securities trading and financial investments (DeYoung and Rice 2004) However, banks are also exposed to various risks associated with their operations, including deposit risks, credit risks, interest rate fluctuations and liquidity constraints In response to these challenges, banks have increasingly adopted multi-sector business models, expanding beyond traditional banking services to investment and other non- traditional activities (Feldman and Schmit 1999) The integration of technological innovation into banking services has further facilitated this diversification, contributing to income growth and risk minimization In an era of increasing global economic integration, such strategic diversification has become essential for banks to remain competitive and resilient in the financial sector
Dynamic capability refers to a firm's ability to continuously reconfigure, integrate, and renew its resources and capabilities to adapt to changing environments, thereby achieving and maintaining a competitive advantage (Teece et al., 1997; Eisenhardt and Martin, 2000) According to Collis (1994), these capabilities determine the speed at which an organization can adapt and enhance its core competencies In digital markets, rapid implementation and being first to market with scalable platforms are crucial, as they enable firms to capitalize on network effects and establish entry barriers for competitors (Osisioma et al., 2016).
Several sub-dimensions of dynamic capabilities have been identified in the literature, with learning and innovative capability being key drivers of strategic renewal Achieving renewal requires organizations to simultaneously explore and learn new methods while exploiting existing knowledge, balancing innovation with efficiency (Osisioma et al.).
2016) Teece et al (1997) see learning as an important process through which experimentation and repetition yield better and quicker resolution to problems enabling firms to realize new production opportunities
Coordination and integration capabilities are crucial for a firm's success, as they enable the assessment of existing resources and the effective combination of these assets to develop new competencies The successful implementation of functional competencies relies on the ability to efficiently coordinate tasks and synchronize activities across different units According to Teece et al., a firm's capacity to integrate and align resources directly impacts its innovation and competitive advantage.
(1997) maintain that a lack of efficient coordination and a combination of different resources and tasks explains why slight economic changes overwhelmingly affects a firm‘s competitive position in a market
Sensing and strategic response capability is crucial for firms to both initiate market change and adapt to external shifts by examining their environment and recognizing new opportunities This capability enables organizations to assess their competitive strengths and respond effectively to strategic moves, which is vital in dynamic markets While challenging, the ability to detect environmental changes and act promptly helps firms update their capabilities before they become outdated or rigid, ensuring sustained competitive advantage (Eisenhardt & Martin, 2000).
Dynamic capabilities are essential for organizational success, particularly in digital transformation, as they emphasize adaptability, strategic renewal, and resource reconfiguration (Osisioma et al., 2016; Teece, 2014) They enable organizations to quickly adapt to changing environments by integrating and transforming internal and external resources (Teece, 2014), supporting continuous strategic renewal through resource reallocation and structural adjustments (Teece, 2016) This framework offers a holistic view that aligns technology adoption with organizational structures, processes, and culture—key factors for successful digital transformation Additionally, dynamic capabilities promote resource flexibility, allowing firms to experiment with innovations and maintain competitiveness (Teece, 2016; Osisioma et al., 2016) They also emphasize alignment with strategic goals, continuous learning, and innovation, making them highly relevant in the ongoing digital era and entrepreneurial growth.
Banks must embrace technological innovation to enhance sustainability and maintain a competitive edge Implementing new technologies improves operational efficiency, expands service channels, and enables quick adaptation to the rapidly evolving digital landscape Leveraging innovative solutions and personalized customer experiences provides a solid foundation for building sustainable competitive advantages in today’s competitive banking industry.
REVIEW OF BANK PROFITABILITY
Bank profitability, as defined by Rose (2002), refers to a bank's net after-tax income or net earnings, usually measured in relation to the bank's size Ezejiofor (2017) emphasizes that profitability reflects a company's ability to generate earnings from its operational activities The efficiency of this profit generation primarily depends on how effectively managers leverage available market resources to optimize performance.
Olalekan and Adeyinka (2013) emphasize that a commercial bank's profitability reflects its operational efficiency and ability to generate financial returns Gürbüz, Yanık, and Aytürk (2013) highlight that banking efficiency is assessed through the bank’s capacity to produce a stable income stream, effectively manage risks, and enhance future profits Berger et al (1997) define bank efficiency as achieving maximum output profits while optimizing the use of input resources Overall, a bank's operational efficiency involves generating profits while minimizing potential risks, with effective management of revenues and costs being essential indicators of efficiency.
Financial ratios are the most widely used method for assessing bank profitability, providing valuable insights into a bank's financial health Studies on Greek commercial banks have shown that financial ratios effectively explain bank performance by analyzing and interpreting financial and accounting data These ratios enable comprehensive evaluation of a bank’s financial situation, facilitate comparisons among banks of different sizes, and serve as industry benchmarks to assess individual performance against industry averages (Guru et al., 2002).
Indicators to measure the profitability of commercial banks
Return on Assets (ROA), Return on Equity (ROE), and Net Interest Margin (NIM) are the most commonly used financial ratios for evaluating bank profitability, as highlighted by numerous studies These key indicators provide valuable insights into a bank's financial performance and overall profitability ROA measures how effectively a bank utilizes its assets to generate profits, while ROE assesses the return generated on shareholders' equity NIM reflects the bank’s core earning ability from its interest-earning assets Understanding these ratios is essential for investors, analysts, and stakeholders seeking to assess a bank’s financial health and performance.
ROA (Return on Assets) is a key financial ratio used to measure a bank’s profitability and overall performance Defined by Rose (2002) as net income divided by total assets, ROA indicates how effectively management generates income from the bank's assets A higher ROA signifies greater efficiency in converting assets into revenue, reflecting strong management performance Consequently, investors and stakeholders prefer higher ROA values, as they demonstrate that the bank is optimally utilizing its assets to achieve optimal profits and overall financial health.
Return on Equity (ROE), defined as net income divided by average total equity, measures a bank's accounting profits generated per dollar of shareholders' equity (Rose, 2002) It reflects the effectiveness of bank management in utilizing shareholders' funds to generate profits A higher ROE indicates efficient management and superior profitability, which benefits shareholders by maximizing their capital investment’s returns.
Return on Equity (ROE) can be broken down into two key components: the equity multiplier and Return on Assets (ROA) The equity multiplier, calculated as assets divided by equity, reflects the leverage used by a bank and is the reciprocal of the capital-to-asset ratio This measure highlights how financial leverage impacts a bank's profitability, making it a crucial factor in financial analysis and SEO-focused content.
In short, ROA measures profitability from the perspective of the overall efficiency of how a bank utilizes its total assets, whereas ROE captures profitability from the shareholders' perspective
The Net Interest Margin (NIM) measures a bank's profitability by calculating the difference between net interest income and net interest expenses, divided by total assets It reflects how effectively a bank manages its core lending and deposit activities, earning interest from loans, overdrafts, and trade finance while paying interest on deposits and liabilities A higher NIM indicates stronger profitability, provided the bank maintains sound asset quality Typically, banks generate income by paying depositors a lower interest rate and lending at a higher rate, and a favorable NIM suggests efficient asset utilization and financial health (San and Heng 2013).
REVIEW OF BANK RISKS
Many economists define risk from a modern perspective as the degree of uncertainty associated with potential events or losses that could significantly impact operations, as described by Peter S Rose (2002) Although risk definitions vary, they all emphasize that risk is inherently linked to uncertainty but remains quantifiable In a competitive economic environment, risk is inevitable because competition is a fundamental characteristic, requiring businesses to adopt effective strategies To sustain and grow steadily, companies must anticipate potential risks, assess their likelihood, and implement preventive measures to mitigate potential impacts.
Income and asset diversification are expected to boost net earnings and reduce credit and interest rate risk Today’s banks emphasize non-interest income because it helps diversify revenue streams and mitigate risk However, DeYoung and Roland (2001) warn that expanding fee-based income may increase profit variability and impact the risk-return balance Conversely, Chiorazzo et al (2008) find that, in European banks, income diversification can lead to higher risk-adjusted returns, with the effects varying depending on bank size.
Risk, in simple terms, refers to uncertain events that can lead to significant losses, especially financial crises for banks While empirical studies highlight advantages such as interest income from lending, securities trading, and financial investments (DeYoung and Rice, 2004), banks also face various risks related to their activities, including deposit, credit, interest rate, and liquidity risks According to Rose (2002), market risks are classified into primary and secondary categories: market risk, credit risk, operational risk, and implementation risk Implementation risk involves losses resulting from weak organizational structures, poor staff supervision, or ineffective management strategies This study primarily focuses on the implementation risk faced by Vietnamese commercial banks.
Indicators to measure the risks of commercial banks
Z-score is a risk measure commonly used in the empirical banking literature to reáect a bankís probability of insolvency It is generally attributed to Boyd and Graham (1986), Hannan and Hanweck (1988) and Boyd et al (1993) and plays an important role in the assessment of both individual bank risk as well as overall financial stability This index is measured as follows:
The Z-score measures the distance to default, indicating how much a bank’s return would need to fall below its expected value to deplete its equity A higher Z-score signifies a lower probability of insolvency, making it a valuable tool for assessing financial stability Its widespread use in cross-sectional studies is attributed to its simplicity and reliance solely on accounting data Unlike market-based risk measures, the Z-score is particularly useful for evaluating both listed and unlisted financial institutions, enhancing its applicability across diverse banking sectors.
A well-diversified portfolio can improve returns and reduce unsystematic risk, but complete elimination of risk is impossible due to numerous external factors affecting financial markets While diversification helps mitigate specific risks, it cannot shield investors from systematic risk, which impacts entire market sectors simultaneously Understanding the limitations of diversification is essential for effective risk management and investment strategy.
REVIEW OF INCOME DIVERSIFICATION
Diversification is a fundamental concept in Markowitz's Modern Portfolio Theory (MPT), emphasizing the importance of spreading investments across different financial instruments, industries, and asset classes to reduce risk The Diversification Effect describes how combining assets with low or negative correlations can effectively diminish overall portfolio risk Understanding the relationship between correlations and risk is essential for optimizing investment strategies and achieving a balanced risk-return profile.
Diversification can be achieved by investing in different stocks, different asset classes (e.g bonds, real estate, etc.) and/or commodities such as gold or oil The objective is to maximize returns and minimize risk by investing in different assets that would each react differently to the same market events Therefore, a well- diversified portfolio should not only consist of multiple stocks from the same industry but also include other asset types, such as commodities or maybe bonds, to mitigate overall risk In more simplistic terms, it relates to the well-known adage
Diversification is a key strategy for reducing risk in banking, as highlighted by the adage “Don’t put all your eggs in one basket” (Fabozzi, Gupta, and Markowitz, 2002) According to Rose and Hudgin (2008), income diversification in the banking industry involves introducing new financial products and services to increase non-interest income as a proportion of total income While traditional banks primarily generate profits from interest income through lending activities, implementing an income diversification strategy involves integrating both interest and non-interest sources, such as fee-based services and commissions This shift enables banks to expand their operations beyond conventional lending, reducing reliance on interest income and enhancing financial stability.
Additionally, Elsas, Hackethal and Holzhọuser (2010) explain that non-interest income restructuring is the restructuring of traditional banking activities such as credit into the form of transaction fees In which, fee collection activities are always stable, creating conditions for commercial banks to develop business channels such as investment, insurance, among others, to increase the ratio of non-interest income to total bank income The research group of Vo Xuan Vinh and Tran Thi Phuong Mai (2015) also approve that income diversification is the increase in the proportion of income from non-interest activities and the gradual decrease in the proportion of interest activities
At commercial banks, non-interest income is currently measured in two ways: the ratio of non-interest income to total bank income and the Herfindahl-Hirshman index (HHI)
Indicator to measure income diversification of commercial banks
Asif and Akhter (2019) pointed out that the HHI index is used by businesses in general and commercial banks when it is necessary to identify the level of competition in the market, whether it is diversified or highly concentrated, HHI is often assessed by competitors in terms of the level of monopoly or oligopoly in the merger and acquisition activities of businesses This index is measured as follows:
Non-interest income (NON) refers to the bank's income derived from various sources such as fees and commissions, service activities, securities trading and investment securities, foreign exchange and gold trading activities, and other miscellaneous activities Net interest income (NET) is the income generated solely from interest activities and is calculated based on the net interest income value within the business results Net income (NETOP) encompasses the total of non-interest income plus net interest income, providing a comprehensive measure of the bank's profitability.
Ratio of non-interest income to total income of banks
Decree 93/2017/ND-CP and Circular 16/2018/TT-BTC establish that commercial bank income comprises both interest and non-interest sources Interest income primarily derives from deposits at other banks or credit institutions, lending activities, and holdings of debt securities, guarantees, or debt trading To reduce reliance on traditional credit operations and mitigate risks from interest rate fluctuations, banks are increasingly emphasizing non-interest income by offering additional financial products and services (Lee et al., 2014).
According to Stiroh (2004), non-interest income primarily originates from foreign exchange transactions, service fees, securities investments, and capital contributions Bank financial statements also reveal income from various other activities, including service operations, foreign currency trading, securities trading and investment, and other miscellaneous activities In essence, income from non-interest activities is composed of three main components, providing a comprehensive measure of a bank's non-interest earnings.
Non-interest income ratio = Net income ratio from business and investment activities + Net income ratio from service activities + Net income ratio from other activities (2.6)
For the scope of this thesis, the author measures income diversification through the Herfindahl Hirschman index (HHI) to calculate and include in the analysis for the research model.
REVIEW OF FINTECH
Fintech refers to the application of technological innovation to deliver financial services, either through entirely new ideas or by reimagining traditional services to streamline transactions and enhance customer access (Le et al., 2021) As a result, Fintech significantly influences the evolution of the banking industry by improving efficiency and expanding financial inclusion.
Recent advancements have driven financial institutions to undergo structural transformations by adopting innovative transaction and distribution systems, enhancing their operational efficiency As a result, banks are significantly increasing investments in ICT infrastructure to stay competitive in the evolving financial landscape.
The increasing adoption of ICT has become one of the most significant trends of the past three decades, serving as a key driver of growth in the knowledge economy ICTs have ignited a digital revolution in developed nations and BRICS countries—Brazil, Russia, India, China, and South Africa—transforming technological landscapes worldwide This rapid spread of ICT influence offers new growth opportunities and prompts major organizational and managerial shifts across industries Financial institutions, including banks, are heavily investing in ICT to improve services through innovations like ATMs, electronic and mobile banking, electronic funds transfers (ETFs), digital currencies, and big data analytics, thereby enhancing customer experience and operational efficiency.
Fintech, or financial innovation, encompasses new products, services, processes, and organizational structures that drive advancements in the financial sector (Frame and White, 2004) According to the Financial Stability Board, it includes innovative business models, technology applications, and operational processes that significantly impact financial markets, institutions, and services (Lee et al., 2021) To effectively measure both the direct effects of Fintech and related factors such as the development environment, human resources, and technology application levels, the Vietnam ICT index plays a crucial role This index assesses key aspects of financial technology, including core banking infrastructure, online payment services, and internet banking platforms, providing a comprehensive view of the financial system's readiness and operational efficiency in the era of digitalization.
This study builds upon the research by Tram Thi Xuan Huong and Nguyen Tu Nhu (2020), which examined the impact of Fintech on bank diversification in Vietnam using the ICT index from the Vietnam Association of Information Technology On April 25, 2015, the Ministry of Information and Communications issued Official Letter No 1275/BTTTT-CNTT to provide data on the ICT readiness and development levels across ministries, government agencies, provincial authorities, economic groups, large corporations, and commercial banks The report evaluates and ranks the ICT application and development readiness of these entities throughout the year, with the ICT index structure outlined in Figure 2.1.
Figure 2.1 Structure of the ICT Index in Banking
(Source: Vietnam Association for Information Processing)
EMPIRICAL REVIEW
Income diversification affecting the bank’s profitability
The study by Chiorazzo, Milani, and Salvini (2008) reveals that income diversification positively impacts bank performance in Italy from 1993 to 2003, especially for large banks Larger banks benefit from economies of scale and better management of leverage and financial services, which stabilize the advantages of diversification (DeYoung & Roland, 2001) However, the benefits tend to decline as banks grow bigger, indicating diminishing returns with increased size For smaller banks, enhancing financial performance through non-interest income is effective only when their initial non-interest income share is low These findings support the argument that income diversification benefits European banks more significantly than some U.S studies suggest, contributing to the ongoing debate between European and American banking systems.
Elsas, Hackerthal, and Holzhӧuser (2010) conducted a comprehensive study using data from nine countries—including France, Germany, Italy, the UK, the USA, Australia, Canada, and Spain—analyzing 380 listed banks with 3,348 bank-year observations from 1996 to 2008 Their research examines the relationship between diversification and bank value, specifically its impact on market-to-book ratios, demonstrating that diversification enhances bank profitability and subsequently increases market value Importantly, this positive effect is independent of whether diversification results from organic growth or mergers and acquisitions The study also highlights key findings such as the non-linear relationship between the cost of equity and diversification, and the positive contribution of fee and trading income from diversification, emphasizing the selectivity of these outcomes.
Céline Meslier, Ruth Tacneng, and Amine Tarazi (2014) demonstrate that income diversification significantly improves bank performance in emerging economies, with a focus on the Philippines Their study, which analyzes data from 39 commercial and universal banks between 1999 and 2005, reveals that banks increasing their non-interest income streams experience higher profitability and better risk-adjusted returns The research highlights that engaging in government securities trading amplifies these benefits, particularly for foreign banks, which gain more from income diversification strategies than domestic banks.
The study by Lee, Hsieh, and Yang (2014) explores how revenue diversification impacts bank performance across different financial structures and reforms Analyzing data from 2,372 banks in 29 Asia-Pacific countries between 1995 and 2009, the research finds that revenue diversification generally enhances bank performance through a portfolio diversification effect The positive impact is more significant in bank-based financial systems, while it remains less clear in market-based systems Additionally, financial reforms such as interest rate controls, banking supervision, and liberalization can influence the relationship between revenue diversification and bank performance, highlighting the importance of financial system context.
While diversification offers clear benefits, several US studies, including DeYoung and Roland (2001), DeYoung and Rice (2004), and Stiroh (2004a, 2004b), as well as European research such as Mercieca et al (2007) and Lepetit et al (2008), suggest that income diversification can reduce bank profits and elevate risk levels.
DeYoung & Roland (2001) found that increased diversification in banks, particularly through higher non-interest income, can lead to reduced profitability due to the need for greater investment in technology and human resources, which raises operating leverage and risk Their research indicates that high leverage significantly influences diversification’s impact, even though bank size was not directly analyzed Banks emphasizing fee-based activities over traditional lending may face higher customer attrition, but overall, traditional operating income remains stable because customer-bank relationships are costly and sensitive to transfer, especially due to private information, making customer loyalty resilient.
Author Stiroh (2004) also conducted research on community banks in the US during the period 1984 - 2000 Aggregate U.S banking industry data were provided by the Federal Deposit Insurance Corporation, meanwhile bank-level data are from the Consolidated Report of Condition and Income The research results showed that when small banks (not corporate banks) diversified their income, it reduced the efficiency of the bank's operations Income diversification for small-sized banks led to reduced profits and increased risks such as commercial and industrial lending activities However, larger banks showed improved profitability when diversifying their income (increased profits and reduced risks) The search for income from non- interest activities brought higher risks because small banks had less management experience than large-sized banks
A study by Mercieca et al (2007) supports the view that income diversification does not enhance bank profits Analyzing data from 755 small European banks between 1997 and 2003 using OLS regression, the research found that these banks do not benefit from diversification The study reveals a negative relationship between non-interest income and risk-adjusted returns, indicating that diversification may not improve profitability for these banks.
Income diversification affecting bank’s risks
Gürbüz, Yanık, and Aytürk (2013) examined the effect of income diversification on risk-adjusted bank performance in the Turkish banking sector between 2005 and 2011, finding that increased non-interest income positively influences financial performance Their study indicates that higher proportions of non-interest income contribute to more stable earnings and improved profitability, supporting modern financial theories on risk diversification However, previous research by DeYoung and Roland (2001) suggests that non-interest income can lead to increased income volatility due to the inherent instability of fee-based and financial transaction incomes, emphasizing the need to carefully evaluate the effects of income diversification within specific market conditions.
The paper by Wang and Lin (2021) examines the impact of income diversification on bank risk in 14 Asia-Pacific economies during the period 2011–
Research from 2016 shows that banks with higher income diversification tend to be less risky, especially in emerging economies, while in developed countries, diversification has no significant impact on risk This suggests that in developed markets, banks may have reached a saturation point in non-interest activities, diminishing the benefits of diversification These findings align with Markowitz’s (1952) portfolio theory and the concept of economies of scope, indicating that diversification can effectively reduce risk by leveraging informational advantages from traditional banking operations.
Hunjra et al (2020) examine how income diversification, corporate governance, and capital regulations influence banks' risk-taking behavior in emerging Asian economies Their study, using GMM analysis on 116 publicly listed banks across 10 countries from 2010 to 2018, reveals that income diversification notably reduces bank risk, especially with the growth of non-traditional income sources like service fees and financial transactions The research emphasizes that effective income diversification combined with well-managed capital regulations can help banks maintain a balance between risk and profitability amid rising competition in emerging markets.
Diversification of loan portfolios into new industries or regions can undermine a bank’s monitoring effectiveness and elevate credit risk, highlighting that diversification does not always guarantee benefits A study by Viral Acharya, Iftekhar Hasan, and Anthony Saunders (2002) examines how focus and diversification strategies influence bank risk and profitability, using data from 105 Italian banks.
Research from 1993 and 1999 shows that diversification does not always result in positive outcomes for banks Industry-based loan portfolio diversification may decrease profitability and heighten risk, particularly for banks with high-risk exposure The effectiveness of diversification strategies is influenced by market competition and a bank’s capacity for risk management.
A 2006 study by Kotrozo and Choi examines how income and geographic diversification impact bank risk and performance across multiple countries Using the Herfindahl index to quantify diversification, the research explores the relationship between focus and diversification strategies with key performance indicators like Tobin’s q, annual stock returns, and total risk The findings reveal that banks concentrating on traditional activities tend to have higher Tobin’s q values than diversified banks, indicating that a focused approach may boost operational efficiency and overall performance.
Kaiguo Zhou (2014) investigates the effect of income diversification on bank risk using data from 62 Chinese commercial banks between 1997 and 2012 The study, grounded in portfolio theory, examines two types of risk: interest income risk and non-interest income risk The findings reveal that income diversification does not have a significant impact on overall bank risk, with a slight decrease in total risk primarily driven by reduced interest-related risks However, non-interest income remains more volatile, contributing more to overall risk Zhou (2014) advises caution in adopting income diversification strategies, as they can carry substantial risks despite potential benefits These results are consistent with Wang and Lin (2021), who found that income diversification has no significant effect on bank risk in developed economies.
Table 2.1 Summary of studies about income diversification Studies Period Research scope Results
All banks which report to the Italian Banking
Income diversification increases risk- adjusted profitability, having a positive impact on profits for banks
Income diversification increases profitability and enhances market value
The shift to non-interest income should boost earnings and risk-adjusted returns, especially as banks engage more in government securities trading
Revenue diversification enhances bank performance through a portfolio diversification effect
472 commercial banks in the US
Income diversfication may not have a positive impact on profitability due to losing customers when participating in fee-based activities
Community banks in the US
Income diversification for small-sized banks led to reduced profits and increased risks such as commercial and industrial lending activities
There is a negative relationship between non-interest income and risk- adjusted returns
Income diversification increases risk- adjusted business performance for the banks in the study sample
Banks in 14 Asia- Pacific economies
Banks with high levels of income diversification are generally less risky, particularly in emerging economies
Effective income diversification and well-managed capital regulations can help banks balance risk and profitability amid increasing competition in emerging economies
Diversification is not always beneficial, it can reduce the effectiveness of a bank's supervision and increase credit risk
Banks with a traditional focus have higher Tobin's q but are riskier than banks with a more diversified income distribution
There is no significant relationship between income diversification and bank risk, although overall risk still tends to decrease but mainly comes from interest rate activities
2.6.2 Research on Fintech (ICT index)
RESEARCH GAP
Research indicates that income diversification and Fintech application influence both profitability and risk; however, the relationship remains inconsistent across studies due to varying research contexts Differences in country-specific economic development, time periods, sample populations, and research methodologies contribute to the contradictory findings Therefore, ongoing research with expanded datasets and diverse observations is essential to clarify these correlations Building on existing studies, this research aims to update and enrich the current understanding of how income diversification and Fintech impact financial performance.
- Inheriting the impact model of Vietnam ICT index on income diversification, with similar indicators to the study of Tram Thi Xuan Huong and Nguyen Tu Nhu (2020)
- Inheriting the research space of 27 Vietnamese commercial banks
- Filling the time gap: The scope of this research topic is in the period 2012 –
In Chapter 2, the author has presented the basic fundamental theories mentioned include: Modern portfolio theory, Theory of financial intermediation, and Dynamic capabilities theory Chapter 2 also introduces the concept and methods of measuring profitability, risks, income diversification and Fintech application At the same time, it explains the role of income diversification and the application of Fintech affecting the operations of Vietnamese commercial banks Moreover, the author synthesizes relevant empirical studies both abroad and in Vietnam with conflicting results for comparison, reference, thereby identifying research gaps Reviewing empirical studies to provide more evidence on the impact of income diversification and Fintech application on bank performance can serve as a basis for studies to help build models and methods, research methods and research hypotheses found worldwide and nationally
Chapter 3 details the research process and methodology used to investigate the factors influencing the banking performance of Vietnamese commercial banks This section outlines how the research model was developed and identifies key variables impacting bank performance, providing a comprehensive framework for understanding the dynamics within Vietnam’s banking sector.
RESEARCH METHOD AND DATA
IMPLEMENTATION PROCESS
The study follows a six-step process to determine the extent and direction of impact The steps are as follows:
Step 1: Identify the Research Problem
Focusing on the research objectives, the author identifies the main issue to be discussed: the impact of income diversification and Fintech on the performance of Vietnamese commercial banks
Step 2: Review Theoretical Foundations, Propose the Research Model and Develop Hypotheses
This article reviews relevant theories and analyzes both domestic and international empirical studies related to the research topic Through comprehensive evaluation of the literature, it identifies key insights that inform the development of a research model Based on this review, the author proposes hypotheses to explore the relationships between independent and dependent variables, providing a solid foundation for the study.
Step 3: Data Collection and Processing
The data used in the study is carefully collected from reliable sources Specifically, data on 27 commercial banks is obtained from audited financial statements on the FinPro system provided by Ho Chi Minh University of Banking, ensuring accuracy and reliability During this process, the author conducts calculations and data processing necessary for running the research model
Step 4: Model Testing Using STATA 17.0
The author conducts descriptive statistical analysis and correlation matrix analysis as an initial step Next, the study applies panel data regression using the
The System Generalized Method of Moments (SGMM) is employed to address potential endogeneity issues within the research model, ensuring more reliable estimations This approach enables an accurate assessment of both the direction and magnitude of the impact that independent variables have on key financial performance indicators such as return on equity (ROE) and Z-score The findings from this analysis provide valuable insights into how these variables influence financial stability and profitability, which will be elaborated upon in the subsequent discussion.
Step 5: Discussion of Research Findings
Based on the results from Step 4, the study presents a detailed discussion on the effects of income diversification and Fintech on the performance of 27 Vietnamese commercial banks The findings are compared and discussed in relation to existing theoretical frameworks and previous empirical studies
Based on comprehensive research findings, the author offers key conclusions and strategic recommendations to improve the performance of Vietnamese commercial banks These suggestions are grounded in both solid theoretical frameworks and practical business insights, aimed at addressing specific research objectives and answering critical questions in the banking sector.
RESEARCH MODEL
Building on previous research by Tram Thi Xuan Huong, Nguyen Tu Nhu (2020), Nguyen Huu Manh, Vuong Thi Huong Giang (2022), Chiorazzo et al (2008), Elsas et al (2010), Nadia Mansour (2020), and Gürbüz et al (2013), the study employs key dependent variables—ROE and Z-score—to accurately measure a firm's profitability and risk-bearing capacity.
This study examines how independent variables such as income diversification (DIV), technology performance (FIN), and their interaction (DIVFIN) influence commercial bank performance Control variables like bank size (SIZE), equity-to-total-assets ratio (ETA), bad debt ratio (NPL), total assets growth rate (GROW), loan loss provision ratio (LLP), and customer loans-to-deposit ratio (LDR) are also considered, along with macroeconomic factors such as economic growth (GDP) Together, these variables collectively impact the financial performance of commercial banks Based on this framework, the author develops a comprehensive research model to analyze these relationships.
This study analyzes the operating efficiency of 27 Vietnamese commercial banks from 2012 to 2023 by measuring their return on equity (ROE) The regression model includes key variables such as the income diversification index (DIVit), the ICT index (FINit), and their interaction (DIVFINit), alongside bank-specific factors like size (SIZEit), total equity to assets ratio (ETAit), and growth rate of total assets (GROWit) Additional control variables encompass the bad debt ratio (NPLit), loan provision to assets (LLPit), customer loans-to-deposit ratio (LDRit), and macroeconomic indicator GDPit The model's parameters include the intercept coefficient, regression coefficients for each independent variable, and random error terms for each bank i over the observed period t.
RESEARCH VARIABLES
Income diversification for banks is assessed based on their income structure, which includes both interest income and non-interest income The study employs the Herfindahl-Hirschman Index (HHI) to measure the level of income diversification, following methodologies established in previous research by Elsas et al (2010), Gürbüz et al (2013), Chiorazzo et al (2008), and Meslier et al.
(2014), Lee et al (2014), Nguyen Minh Sang (2019), Tram Thi Xuan Huong and
Nguyen Tu Nhu (2020) and more The degree of diversification is calculated according to the following formula:
NET: Interest income is measured by net interest income
Net Non-Interest Income (NOI) encompasses key revenue streams such as net fee and commission income, gains or losses from foreign currency trading, trading securities, and investment securities It also includes net income from other banking activities, capital contributions, and share purchases, reflecting the bank's diversified sources of non-interest earnings.
NETOP: Net income is determined as the sum of net interest income and net non-interest income:
The Herfindahl-Hirschman Index (HHI) coefficient ranges from 0.5 to 1, which means the Diversification (DIV) coefficient varies from 0 to 0.5 A DIV value of 0 indicates that commercial banks generate income from a single source, reflecting low diversification Conversely, as the DIV approaches 0.5, it signifies higher diversification, meaning banks have multiple income sources This relationship highlights the importance of diversification in assessing the income stability and risk profile of commercial banks. -**Sponsor**Struggling to rewrite your article and ensure it's SEO-friendly? It can be tough! With [Article Generation](https://pollinations.ai/redirect-nexad/XCUDlBUc), you can instantly get 2,000-word SEO-optimized articles that capture the essence of complex ideas, like explaining the HHI and DIV coefficients, without the hassle of manual rewriting Imagine saving over $2,500 a month compared to hiring a writer It's like having your own content team, ready to help you clarify and optimize your message!
Income diversification theories examine the benefits and costs associated with a bank's growth strategies, highlighting how diversification improves financial efficiency as a bank expands its scale and scope of operations Numerous studies, including research by Chiorazzo et al (2008) and Lee et al., demonstrate a positive relationship between income diversification and enhanced financial performance, underscoring its significance in banking industry success.
Research indicates that while some studies suggest that income diversification can enhance bank performance, others have found a negative relationship between diversification and financial outcomes Diversification can lead to increased income volatility, as certain revenue streams become more unstable Additionally, diversification efforts often reduce customer switching costs and raise operating leverage due to fixed asset investments like technology infrastructure These factors collectively contribute to higher risk and greater income variability for banks (DeYoung and Roland, 2001).
DeYoung and Rice (2004) and Stiroh (2004) highlight that an increase in diversification income (DIV) leads to higher income diversification in banks Theoretical foundations and prior research suggest that greater income diversification positively impacts bank profitability and financial stability Therefore, enhancing income diversification can be a strategic approach to improve overall financial performance and stability in banking institutions.
The ICT index, representing fintech or technology adaptation in Vietnamese banks, is calculated based on data from the Vietnamese Technology Association spanning 2012 to 2023 This index, or FIN variable, reflects a bank's investments in digital infrastructure, technological innovation, and automation These investments are vital for improving operational efficiency, customer service, and risk management While increased ICT spending can boost profitability through enhanced efficiency and revenue growth, it may also introduce financial and operational risks that could impact the bank's stability According to both theoretical and empirical research, it is expected that the impact of FIN on bank profitability and financial stability is predominantly positive.
This study introduces a new variable to examine the impact of Fintech on the relationship between income diversification and banking performance Specifically, it investigates how banks with a high ICT index influence this relationship compared to other banks Based on findings from Tram Thi Xuan Huong and Nguyen Tu Nhu (2020), the ability to leverage information technology positively impacts bank diversification Consequently, the interaction variable DIVFIN is expected to have a positive effect on both profitability and financial stability in the banking sector.
Bank size is determined by taking the natural logarithm of total assets, measured in millions of VND, at the end of the financial year This method is widely used in research to assess the scale of commercial banks (Gürbüz et al., 2013; Lee et al., 2014).
( ) (3.5) Larger banks tend to be more stable as individual risks diminish with scale They are also more likely to invest in modern technology and expand their business operations (Meslier et al 2014) This perspective is supported by studies such as Elsas et al (2010), Nadia Mansour (2020), Gürbüz et al (2013), Chiorazzo et al
(2008), Zhou(2014), Kotrozo and Choi (2006), Hunjra et al (2020) among others However, Meslier et al (2014) concluded that there is an inverse relationship between bank size and financial performance Based on theory and previous research, the author expects the impact sign of SIZE on profitability and risks in both models 1 and 2 to be positive Consequently, many studies point out that total assets has a positive effect on profitability and financial stability
Total assets growth is calculated by the present by the ratio of total assets year t minus the total assets year t-1, divide total assets year t-1 of commercial banks
The total assets growth (GROW) variable indicates the annual percentage increase in a bank’s total assets and reflects its expansion strategy, loan portfolio growth, and overall business development (Chiorazzo et al., 2008; Elsas et al., 2010; Meslier et al., 2014; Nguyen Huu Manh & Vuong Thi Huong Giang, 2022; Tram Thi Xuan Huong & Nguyen Tu Nhu, 2018) While increased total asset growth can boost profitability by expanding income-generating activities, it may also increase financial risk and volatility, potentially compromising financial stability (Gurbuz et al., 2013) Based on these theories and prior research, the GROW ratio is expected to have a positive effect on both bank profitability and financial stability.
Equity to total assets ratio (ETA)
Equity to total assets ratio is measured by the ratio of equity-to-total-assets, data collected at the end of the financial year of commercial banks
Equity-to-total-assets ratio (ETA) represents the financial leverage of a bank
The equity-to-total-assets ratio reflects a bank’s financial strength and market position, indicating its capacity to withstand economic fluctuations Banks with a higher ratio face lower risks and tend to deliver stronger financial performance Greater equity capital reduces reliance on external funding and is associated with lower leverage, thereby minimizing financial risk According to research by Zhou, higher equity levels enhance a bank’s stability and resilience in volatile markets.
(2014), Nguyen Huu Manh and Vuong Thi Huong Giang (2022) and Lee et al
Research by 2014 indicates a positive relationship between the equity-to-total-assets ratio and financial performance, highlighting its importance for profitability and financial stability However, Anbar and Alper (2011) reported no significant link between this ratio and financial performance, suggesting mixed findings in the literature Overall, previous studies suggest that maintaining an optimal equity-to-total-assets ratio can enhance a company's profitability and financial stability, making it a key indicator for financial analysis.
Customer loans-to-deposit ratio (LDR)
The customer loan-to-deposit ratio is calculated using a specific formula, providing a key indicator of a bank's liquidity and lending efficiency This data is derived from the bank's audited financial statements at the end of the fiscal year, ensuring accuracy and reliability Monitoring this ratio helps assess the bank’s ability to meet its customer loan demands relative to its deposit base, which is essential for financial analysis and risk management.
DATA
This study utilizes data primarily from the FiinPro platform provided by Ho Chi Minh University of Banking, with missing information supplemented by analyzing Vietnamese banks' annual financial statements submitted to the State Bank of Vietnam The sample includes 27 Vietnamese commercial banks covering the years 2012 to 2023 For the Vietnam ICT Index, data is collected from the Vietnam ICT Annual Reports available on the Vietnam Association for Information Processing website Missing data for 2021 and 2023 are addressed using simple linear interpolation, averaging adjacent years’ values, while linear extrapolation estimates 2024 values based on historical growth trends, assuming consistent growth without abrupt changes. -**Sponsor**Sounds like you're looking to polish up your article and ensure it's SEO-friendly! Creating coherent paragraphs with impactful sentences is key Speaking of content creation, have you explored how [Article Generation](https://pollinations.ai/redirect-nexad/5puGONML) can help? Imagine getting SEO-optimized articles instantly—it could save you a ton of time and money compared to manual rewriting and hiring writers! It's like having your own content team, ready to enhance your work and boost its impact.
THE RESEARCH METHODOLOGY
According to Gujarati (2004), a correlation coefficient exceeding 0.8 between independent variables indicates a high risk of multicollinearity, which can distort regression coefficients and lead to unreliable research outcomes To prevent this, researchers should examine the correlation matrix and assess multicollinearity using Variance Inflation Factors (VIF) before running the regression model A VIF value below 10 suggests that multicollinearity is not a significant concern, ensuring the integrity of the model's estimations.
This study employs Pooled Ordinary Least Squares (Pooled OLS) to analyze panel data, integrating methods such as Fixed Effects Model (FEM), Random Effects Model (REM), Feasible Generalized Least Squares (FGLS), and Generalized Method of Moments (GMM) The research examines the influence of income diversification on the financial performance of commercial banks, providing comprehensive insights into how diversified income sources impact banking profitability and stability By applying these advanced econometric techniques, the study offers robust evidence on the relationship between income diversification strategies and overall financial outcomes in the banking sector.
The Pooled-OLS model is suitable when there are no individual bank-specific or time-specific effects In contrast, FEM and REM estimation methods account for both time factors and individual bank effects, making them more appropriate for regression analysis when such factors are present To determine the most fitting regression model among Pooled-OLS, FEM, and REM, various statistical tests are employed to ensure the best model fit.
F-Test: to choose Pooled OLS or FEM model When the P-value ≤5%, the FEM model is selected
Hausman test: to choose between FEM and REM models When the P-value
≤5%, the FEM model is selected and vice versa, P-value ≥5%, the REM model is selected
Breusch and Pagan test: to choose OLS and REM, when P-value ≤5%, choose REM model, otherwise choose OLS model
After selecting the appropriate model, the study continues to perform the autocorrelation and heteroscedasticity o Autocorrelation testing
Ho: The model does not have autocorrelation
According to Wooldridge (2002), if the P-value ≤5%, then reject the hypothesis H0, that is the model has autocorrelation phenomenon o Heteroscedaticity testing
Ho: The model does not have the phenomenon of Heteroscedasticity
H 1 : The model has the phenomenon of Heteroscedasticity
If the P-value is less than or equal to 5% (P-value ≤ 5), then the hypothesis H0 is rejected, meaning that the model has the phenomenon of Heteroscedasticity
If a model exhibits autocorrelation and heteroskedasticity, the Feasible Generalized Least Squares (FGLS) method can effectively address these issues by controlling for autocorrelation and variable variance However, FGLS accuracy diminishes when the model includes lagged or endogenous variables In such cases, the Generalized Method of Moments (GMM) is the most reliable approach, as it overcomes the limitations of FGLS and provides more precise estimations for models with endogenous variables Additionally, conducting endogenous variable testing is essential to ensure the validity of the model's results and its suitability for GMM estimation.
If the P-value is less than or equal to 5%, it indicates that the null hypothesis (H0), which suggests the variable is endogenous, should be rejected Conversely, if the P-value exceeds 5%, we accept the null hypothesis, concluding that the variable is exogenous This threshold helps determine the nature of the variable based on statistical significance.
GMM method is suitable for panel data and overcomes the phenomenon of endogenous variables when the following conditions are met:
Firstly, Number of instruments < Number of groups
The Hansen and Sagan tests assess the validity of the instrumental variable by testing whether it is exogenous and uncorrelated with the error term in the main model Both tests operate under the null hypothesis (Ho) that the instrumental variable is exogenous, meaning no correlation with the error term A higher P-value in these tests indicates stronger evidence supporting the null hypothesis, and thus, the instrument’s validity improves as the P-value increases Therefore, the significance level in Hansen and Sagan tests is crucial for confirming the reliability of the instrumental variable in econometric analysis.
Thirdly, AR2 > The significance level of the AR2 test is important because this test overcomes autocorrelation in the model
Chapter 3 presents the research methodology in order of steps in the research process from approach, data collection method and data processing method
Accordingly, through the panel data regression model approach proposed in Chapter
The author develops a comprehensive model using data collected from the FiinPro system, annual Vietnam ICT reports, and the financial statements of banks within the study scope This research model aims to analyze key financial and technological indicators to provide valuable insights By integrating diverse data sources, the model enhances accuracy and relevance for assessing bank performance and the impact of ICT innovations in Vietnam’s banking sector.
On the other hand, in the following Chapter 4, the author will provide a more comprehensive overview of the results obtained from the research process
The article presents data, charts, and tables to analyze the impact of income diversification and Fintech on bank performance, providing a comprehensive understanding of their significance Utilizing quantitative research methods, including descriptive statistics, comparative analysis, and linear regression techniques such as OLS, FEM, REM, and FGLS, the study offers a rigorous evaluation of these factors' influence on banking success.
GMM models, the author will choose the most suitable model Finally, from these results, the author will compare them with the finding of previous empirical studies.