ĐẠI HỌC KINH TÉ THÀNH PHỐ HÒ CHÍ MINHBÁO CÁO TÔNG KẾT “NHÀ NGHIÊN CỨU TRẺ UEH ” NĂM 2024 SUSTAINABLE DEVELOPMENT: DOES INFORMATION AND COMMUNICATION TECHNOLOGY HAVE AN IMPACT ON STABILIT
INTRODUCTION
Research rationale
In today's digital age, Information and Communication Technology (ICT) is crucial for global connectivity and societal development The rapid growth of the Internet, mobile devices, and communication advancements has transformed ICT into a key driver of innovation across various sectors, including education, healthcare, and manufacturing Emerging technologies such as Artificial Intelligence, the Internet of Things, and Blockchain are revolutionizing automation and process optimization, creating new opportunities for individuals and businesses alike ICT is integral to essential human activities, influencing everything from communication to complex pursuits like space exploration and scientific research Moreover, the banking and financial sectors are significantly impacted by ICT, as they serve as the backbone of economic growth Countries that fail to harness and implement effective technology risk stagnating in their social, economic, and cultural progress.
The accessibility of Information and Communication Technology (ICT) in households significantly influences financial inclusion in West Africa, as highlighted by Karakara and Osabuohien (2019) It affects how families engage with financial services, with its dynamics shaped by various socioeconomic factors Policymakers must create strategies to improve ICT access and increase awareness of the importance of banking services The notable differences in ICT adoption rates between countries like Burkina Faso and Ghana underscore the need for customized approaches to effectively promote financial inclusion.
The banking sector has experienced a transformative shift due to the influence of Information and Communication Technology (ICT), significantly enhancing accessibility, inclusion, efficiency, and profitability in financial services Research indicates that ICT improves customer service delivery, facilitates accurate record-keeping, and provides convenient and faster banking services, thereby strengthening the competitive edge of the economy As the backbone of a robust economy, the banking industry’s stability is crucial, with disruptions leading to far-reaching economic consequences, as seen in recent crises faced by European banks The impact of globalization, intense competition, and ongoing innovation underscores the need for a deeper understanding of consumer behavior in shaping banking responses Ultimately, the integration of ICT has not only revolutionized financial service delivery but has also become a key driver of the industry's ongoing evolution.
Evaluating the digital transformation of commercial banks is essential for enhancing their overall performance (Xuanli Xie, Shihui Wang, 2023) An index system that encompasses strategy, business, and management transformations serves as a crucial tool for quantitative research within the digital economy Policymakers must emphasize the importance of digital transformation for banks to maintain a competitive edge in today's digital landscape Future research should explore the economic implications of digital transformation, including its effects on bank competition, credit supply, inclusive finance, and regional economic impact.
The banking sector in Vietnam has achieved significant milestones due to the influence of ICT, notably with Vietcombank's introduction of Automated Teller Machines (ATMs) for public use in the early 2000s, which paved the way for widespread ATM availability across the country, providing 24/7 access to banking services Additionally, Techcombank launched Vietnam's first online banking platform in 2007, marking a pivotal moment in the adoption of digital banking services, which have since become essential and widely accessible to the public.
The impact of Information and Communication Technology (ICT) on the banking sector remains complex and multifaceted, despite increased research efforts While ICT enhances borrower analysis and operational efficiency, it also introduces new risks, such as disruptive competition from fintech companies This dual nature of technological advancement highlights the necessity for further investigation to aid policymakers and regulators in adapting to the shifting banking landscape In Vietnam, the growth of ICT in banking operations underscores the urgency to study its effects on the industry's stability Therefore, our research aims to clarify the intricate relationship between ICT and the banking sector, providing insights into its diverse influences.
This study investigates the impact of the ICT index on the banking system, focusing on its potential to enhance information distribution and its relationship with bank stability Additionally, we analyze how national ICT development, influenced by various control variables, affects the stability of banks.
Research objectives and research questions
Our research aims to analyze the impact of Information and Communication Technology (ICT) on the banking industry in Vietnam We conduct an in-depth examination of the complex relationship between ICT and the sustainable development of banks, highlighting how technological advancements can transform banking operations This transformation is essential for enhancing the long-term viability and resilience of banks in an ever-evolving financial landscape.
Our research explores the national-level impact of ICT development on bank stability, aiming to offer a comprehensive view of how technological advancements can either enhance or undermine the stability of financial institutions, ultimately affecting the wider economy.
Our research delves into the internal dynamics of individual banks and their significant influence on overall stability This aspect of our study highlights the micro-level factors that are crucial in determining the resilience and sustainability of banks as they adapt to changing technological environments.
Our research presents a detailed exploration of ICT strategic development, starting at the organizational level and extending to national implications, while also examining the internal dynamics of individual banks This multifaceted approach offers a nuanced understanding of the complex factors that influence the sustainable development and stability of banks in a rapidly evolving technological landscape.
Based on the research objective just mentioned, the research questions in the study include:
I What impact will the level of banks' development in ICT have on the bank's stability?
2 How does ICT development at the national level affect the bank industry stability in Viet Nam?
3 How do the internal characteristics of each bank impact the bank's stability?
From there, we make the following hypotheses to prove our objectives:
Hi: Development in ICT (represented by the ICT Index variable with data assessed by Vietnam’s Ministry of Information and Communications) has a positive impact on the stability of banks.
H?: The internal characteristics of each bank has a positive impact on the stability of the banking industry.
H3: ICT development at the national level which is measured by domestic credit variable has a negative impact on the stability of banks.
Research subject and scope
The paper utilizes balanced panel data from 26 banks in Vietnam for the period from
From 2009 to 2020, the analysis incorporates various metrics, including bank stability indicators such as Return on Equity (ROE), Return on Assets (ROA), and Z-Score Additionally, the ICT index, which assesses the readiness for IT development and application, is sourced from the Ministry of Information and Communication The study also considers bank-specific variables like Equity to Total Assets (ETA), bank size, and Loan Loss Provisions (LLP), alongside country-level factors such as GDP, inflation rates, domestic credit, and infrastructure related to ATMs, mobile registration (with populations exceeding 100), internet access, fixed broadband, and fixed telephone services.
This study utilizes regression analysis to explore the relationship between Information and Communication Technology (ICT) and bank stability, while accounting for various control variables The objective is to present empirical evidence supporting the positive link between bank profitability and the ICT index, emphasizing the significant role of ICT in improving bank performance in Vietnam.
Research methodology
The study employs panel data analysis to examine the role of ICT development in shaping financial institutions, especially bank's stability in Vietnam The process involves these steps:
2 Gather the necessary data for the analysis.
3 Testing related to regression models
4 Perform different statistical tests, validate data, select a fitting regression model, and address any model-related concerns.
5 Verify test results and interpret research findings
Research structure
This chapter outlines the reasons for choosing the research topic, defines the research objectives, identifies the research subjects, and delineates the scope of the study Additionally, it offers an overview of the research methodology and highlights its importance in achieving the study's goals.
LITERATURE REVIEW
Theoretical background
2.1.1 An overview of Information and Communication Technology
Information and Communications Technology (ICT) refers to the infrastructure and components that enable modern computing Its primary goals are to improve the ways individuals create, process, and share information, while also enhancing skills across various sectors, including business, education, healthcare, and entertainment By leveraging ICT, users can solve real-world problems and engage in diverse activities such as sports, music, and movies more effectively.
The definition of Information and Communication Technology (ICT) is not fixed, as it evolves alongside advancements in technology and related concepts Generally, ICT encompasses all devices, networking components, and applications that work together to facilitate interactions for individuals and organizations in the digital landscape.
Information and Communication Technology (ICT) refers to the comprehensive landscape shaped by the internet and mobile networks, integrating both traditional technologies like landline phones, radio, and television, as well as cutting-edge innovations such as artificial intelligence and robotics This broad term encompasses any technology, infrastructure, or device that enables communication, data sharing, and connectivity on a global scale, facilitating interactions between people and machines.
ICT is rapidly evolving due to transformative technologies such as the internet, the Internet of Things, and the Metaverse These advancements, combined with cloud computing, video conferencing tools, and unified communications systems, have fundamentally changed the way we connect, access information, and collaborate.
The future of Information and Communication Technology (ICT) is poised for remarkable advancements with the rollout of 5G and 6G networks, the decentralized vision of Web3, and the groundbreaking potential of quantum computing These innovations are set to deliver faster connectivity, enhanced data security, and transformative experiences in virtual and augmented reality.
Relationship between ICT development and bank's stability - “Efficiency and
While cost reduction is a key benefit, ICT provides commercial banks with a wider array of advantages, including enhanced efficiency, improved customer experience, better risk management, and increased innovation By effectively utilizing technology, banks can successfully navigate the changing financial landscape and achieve long-term success A study by Kozak, covering 1992 to 2003, highlighted the significant impact of ICT evolution on the profitability and cost-effectiveness of the banking system, demonstrating its positive influence on overall performance and efficiency in the sector.
Information and Communication Technology (ICT) serves as a powerful double-edged sword for bank stability by enhancing operational efficiency and expanding access to new customer segments Automation and data-driven insights enable banks to reduce costs, minimize operational errors, and optimize resources, strengthening their capital buffers to better withstand financial challenges However, ICT also drives disruptive innovation and intensifies competition, leading to new products and services that may increase risk-taking behavior and heighten the potential for systemic contagion through interconnected networks Consequently, effectively navigating the ICT landscape requires a careful balance between harnessing its efficiencies for resilience and managing the competitive pressures it creates, ensuring that technological advancements contribute to the long-term stability of individual banks and the overall financial system.
Alternative studies suggest that focusing too heavily on technology investment may not be beneficial when assessing efficiency and cost theories Simply acquiring technology does not automatically improve banking operations' efficiency, as operational weaknesses in technology management and a lack of effective utilization of technological advantages hinder organizational goals.
The integration of technology with human elements can increase organizational complexity, making it harder to maintain a competitive advantage and potentially diminishing the unique characteristics of the bank over time.
The relationship between ICT development and stability is complex and not always straightforward Excessive dependence on technology can lead to new risks, and ineffective ICT implementations may yield adverse outcomes Therefore, banks must take a strategic and balanced approach, ensuring that their investments in ICT are aligned with their business objectives and risk management strategies.
In summary, grasping the theoretical basis of the link between banks' ICT development and stability is essential for informed technology adoption and financial risk management By effectively utilizing ICT, banks can boost efficiency, reduce risks, strengthen customer relationships, and achieve a competitive advantage, all of which significantly enhance their financial stability and resilience.
The evolving role of Information and Communication Technology (ICT) has significantly influenced the efficiency and stability of the Vietnamese banking sector Despite valuable insights from previous studies, there remain gaps in understanding how specific perspectives on ICT affect these critical areas This section will explore these perspectives and critically analyze existing research to illuminate the complexities of ICT's impact on banking Our goal is to inform future research and develop practical strategies to fully leverage ICT's potential in enhancing Vietnam's financial landscape.
RESEARCH METHODOLOGY
Data collection
This research conducted a thorough evaluation of the impact of Information and Communication Technology (ICT) on the stability of the banking sector, utilizing a comprehensive data collection strategy Financial data from 26 commercial and state-owned banks spanning eleven years (2009-2020) was carefully compiled from their financial statements Additionally, ICT Index data for the same period was obtained from the Ministry of Information and Communication This meticulous approach resulted in a substantial dataset of 203 observations, which were rigorously analyzed using the reputable STAT A 16 software Further details on variable specification will be discussed in the subsequent section.
Variables data and description
This investigation employs a twofold approach to assess bank stability by analyzing the risks faced by banking organizations using the Z-score, and evaluating profitability through Return on Assets (ROA) and Return on Equity (ROE) indicators The data for these independent variables were sourced from the Refinitiv Eikon database, which compiles financial information from the statements of 26 commercial and state-owned banks.
This research applies the Z-score index to measure risk in banks, referencing prior work by Laeven & Levine (2009) The Z-score is a key metric in the banking industry for evaluating financial health and risk exposure Originally developed by Edward Allman in the 1960s to predict bankruptcy in non-financial corporations, it has since been adapted for the banking sector The Z-score incorporates various financial ratios to assess a bank's solvency and default risk.
The calculation formula of Z-score is represented as follow:
The Z-score is a crucial indicator of a bank's stability, with a higher Z-score signifying a lower likelihood of default, thereby enhancing the bank's financial security Conversely, a lower Z-score suggests an increased risk of default, which can negatively affect the bank's stability Key components influencing the Z-score include the return on assets (ROA), the equity to asset ratio, and the standard deviation of the return on assets.
Bank profitability - Return on Assets (ROA)
Return on Assets (ROA), is a financial ratio that measures how efficiently a bank uses its assets to generate profit It is essentially a profitability metric expressed as a percentage.
The calculation formula of ROA is represented as follow:
A higher ROA indicates a bank is generating more profit per value of assets it owns This generally implies better stability to the bank.
Bank profitability - Return on Equity
Return on Equity (ROE) is a vital financial metric for evaluating a bank's performance and efficiency, as it indicates the profit generated in relation to shareholder equity The formula for calculating ROE is straightforward, providing insights into the bank's ability to utilize equity effectively.
A higher ROE indicates the bank is generating more profit per value of shareholder equity This generally implies good returns for bank’s shareholders and strengthening stability.
The advancement of Information and Communication Technology (ICT) has significantly transformed the banking industry, intensifying competition among banks (Vives & Ye, 2023) This study will utilize the ICT index as a key explanatory variable, as outlined by Le, T.L.V & Pham, D.K (2022) Published by the Ministry of Information and Communications of Vietnam, the ICT index assesses the readiness for ICT development and application within banks, offering insights into their ICT status and performance rankings The index is derived from an average of four component indices: ICT infrastructure, ICT human resources, internal bank ICT applications, and online ICT services for customers, with each component calculated using a specific set of indicators.
ICT index = “ (ICTinsfrastructure + ICThliman resources + ICT internal bank application + ICTonline services)
According to the ICT index report from the Ministry of Information and Communications of Vietnam, each component index is comprised of specific indicators that are calculated and integrated into the overall index.
1 Percentage of Virtual Servers/ Total Number of Servers (Physical Servers + Virtualized Servers).
2 Percentage of workstations (PC/Laptop) in the last 3 years/Total number of workstations.
3 Percentage of workstations running a copyrighted operating system and having manufacturer support (For example: For Windows Operating System, from Windows 7 version or higher).
4 Percentage of Internet bandwidth provided to internal users/ Total number of computers connected to the Internet.
5 Percentage of Internet bandwidth providing Internet Banking services/Total number of Internet Banking customers.
6 Percentage of wide area network bandwidth/Total number of terminal computers.
7 Percentage of ATM machine/Total number of payment cards.
8 Percentage of POS machine/Total number of payment cards.
9 Deploy information security and data safety solutions Calculated by information security services for each type of ICT application over the corresponding total number of ICT devices
10 Data Center and Disaster Prevention Center Calculated by 5 X Data Center + 3
X Disaster Prevention Center + Disaster Prevention Center)
ICT human resources - including 3 indicators
1 Percentage of specialized ICT Staff/Total employees.
2 Percentage of employees responsible for information security/ Total number of specialized IT staff.
3 Percentage of specialized IT staff with international IT certification/Total number of specialized IT staff.
Internal bank ICT application - including 3 indicators
1 Implement Corebanking Calculated by sum of total Corebank modules, total Corebank connections, system connections, level of automation when processing transactions between Corebank systems and other systems, data reconciliation between CoreBank and other systems.
Online ICT services provided to customers - including 5 indicators
2 Internet Banking for individual customers.
3 Internet Banking for business customers.
Internal factors significantly influence bank profitability, as highlighted by Rahman (2015) This study expands on the research model by Le and Pham (2022) by examining bank-specific variables to explore their relationship with the overall stability of the banking industry.
The analysis focuses on key bank-specific variables, including Size, measured by total assets, Equity to Total Assets (ETA), calculated by dividing equity by total assets, and Loan Loss Provisions (LLP), which reflect the provisions for loan losses relative to total loan value These indicators are essential for evaluating the financial health of banks and their influence on industry stability Data for these variables was obtained from the Refinitiv Eikon database.
Macroeconomic variables significantly impact bank profitability and the stability of the financial industry This study, inspired by the research model of Le, T.L.V & Pham, D.K (2022), examines two key macroeconomic indicators: the growth rate of Vietnam's Gross Domestic Product (GDP) and the nominal inflation rate (INF) Data for these variables were sourced from the World Bank open database, covering the period from 2009 to 2020.
3.2.5 ICT country- level control variables
This study incorporates country-level Information and Communication Technology (ICT) variables alongside the ICT index to analyze their impact on the overall stability of the banking industry from a macro perspective Drawing inspiration from Ha, M.S & Nguyen, T.L (2022), we utilize five key ICT factors sourced from the World Bank open database to enhance our understanding of ICT's role in the banking sector.
Fixed broadband measures the number of subscriptions per hundred individuals in a population, serving as an indicator of the accessibility of broadband services in a country The fixed telephone variable reflects the percentage of registered landline phones compared to the total population, assessing landline usage and adoption The internet variable indicates the percentage of individuals using the internet within a population, offering insights into internet connectivity levels Additionally, the Automated Teller Machines (ATMs) factor evaluates the ratio of ATMs to the total number of bank branches, highlighting ATM accessibility Finally, the mobile variable represents mobile subscriptions per hundred residents, indicating the prevalence of mobile phone usage in a nation.
Research model and variables description
This research employs a quantitative causal associative approach to analyze the significant influence of Information and Communication Technology (ICT) on the financial sector Drawing on established theoretical frameworks, it highlights ICT as a crucial driver for financial institutions, offering numerous opportunities to innovate existing business models Notably, ICT enhances the capacity of financial actors by improving credit allocation and promoting a more competitive market environment Therefore, investing in ICT is essential for developing effective risk management strategies and ensuring sustainable growth for financial institutions, especially banks.
Drawing inspiration from the model introduced by Le, T.L.V & Pham, D.K (2022) with the addition of ICT country-level control variables from Ha, M.S & Nguyen, T.L
(2022) model which delves into the impact of digital transformation to the banking industry in Vietnam, the authors construct the following research regression model:
Bank stability^ po + piICTIndexJ- p ETA„ + p,Size„ + p,LLP„ + p(GDP, + pJNF„
+ p ATMit + p.Domcsticrcdit, + p.Fixcdbroadband, + pjnternetu + piiMobile + sit
The study analyzes the stability of 26 banks using a regression equation that incorporates key financial metrics, including Return on Equity (ROE), Return on Assets (ROA), and ZScore The primary variable, the ICT Index, assesses each institution's readiness for ICT development and implementation Additionally, the research examines bank-specific characteristics such as the equity-to-assets ratio (ETA), total assets (Size), and provisions for loan losses (LLP) Macroeconomic factors, including economic growth (GDP), nominal inflation rate (INF), and domestic credit to private sectors (Domesticcredit), are also included as supplementary controls.
The article outlines five key ICT country-level variables: Fixed broadband measures the number of subscriptions per 100 people, while fixed telephone accounts for the percentage of landline registrations per 100 individuals Internet usage is represented by the percentage of users relative to the total population The ratio of Automated Teller Machines (ATMs) to total bank branches indicates ATM availability, and mobile subscriptions are quantified as the number of subscriptions per 100 inhabitants A comprehensive overview of these variables and their anticipated outcomes is detailed in Table 1.
Table 1 Variable list, description and prediction
Type variable Name Definition Expected sign
ROA Profit after tax / total assets
ROE Profit after tax/equity
Z-Score (ROA + ETA) / ROA Standard Deviation
Communication Technology (ICT), Rated and collected from Vietnam's Ministry of Information and Communication.
Size On the log value of a bank's total assets (+)
LLP Provision of loss loans / total loans (+)
GDP Gross Domestic Product growth (+)
Domestic credit Domestic credit to the private sector (% GDP) (-)
ICT country level control variables
ATM Number of ATMs (on 100.000 people) (+)
Fixed broadband subscription (over 100 people)
Fixed telephone Landline registration (over 100 people) (+)
Internet Individuals using the Internet (% of the population)
Mobile Mobile registration (over 100 people) (+)
RESEARCH RESULT AND DISCUSSION
Statistical Description
After collecting and analyzing the data, the results are summarized in the table below, which employs descriptive statistical measures This table displays the number of observations, as well as the mean and standard deviation for each variable used in the study.
Table 2 Descriptive statistics table of variables
Variable Obs Mean Std Dev Min Max
Variable Obs Mean Std Dev Min Max
The dataset's robustness is highlighted by the uniform distribution of its variables and a substantial sample size of 203 observations A large sample size is crucial for statistical analyses, as it improves the precision and validity of findings, enabling more confident generalizations about the broader population This extensive dataset serves as a strong basis for deriving meaningful insights and conclusions, minimizing the risk of spurious or unreliable results that smaller samples may produce.
The model incorporates 18 variables, highlighting the complexity and richness of the dataset This diversity enables a thorough exploration of interrelationships and dependencies among the variables, leading to a deeper understanding of the underlying patterns Additionally, the suitability of the input data for regression analysis paves the way for investigating predictive relationships between these variables.
The analysis of the table reveals minimal dispersion in the model's variables, indicating a homogeneous data distribution The standard deviations closely align with their means, demonstrating that the values for each variable are tightly clustered around the average, which reflects a consistent and stable pattern.
Correlation matrix
Table 3 Correlation matrix of variables
ZScore ROA ROE ICTIndex SIZE ETA LLP GDP INF ATM Domesticcredit
The correlation matrix reveals a significant relationship between ICT development and bank performance, indicating that advancements in ICT notably enhance key metrics such as Return on Assets (ROA) and Return on Equity (ROE) This positive correlation underscores ICT's role as a crucial driver of efficiency and success in the banking sector Furthermore, these findings align with the research conducted by Le, T.L.V & Pham, D.K (2022), which also emphasizes the beneficial impact of ICT on bank stability Detailed relationships among other variables in the model are outlined in the accompanying table.
Arellano- bond lest
Table 4 First-orderArellano-Bond test, AR(1)
Ho: The model has no first-order serial correlation.
Model (1): ZScore Model (2): ROA Model (3): ROE z 0.84 z -1.74 z -1.91
The AR(1) test results indicate that all models have a Pr>z value exceeding 5% Consequently, we accept the null hypothesis (Ho), confirming that the models do not demonstrate first-order serial correlation.
Table 5 Second-order Arellano-Bond test, AR(2)
Ho: The model has no second-order serial correlation.
Model (1): ZScore Model (2): ROA Model (3): ROE z -0.77 z 1.09 z 0.95
The AR(2) test results indicate that all models have a Pr>z value exceeding 5%, leading to the conclusion that the null hypothesis (Ho) is accepted Consequently, this suggests that the models do not display second-order serial correlation.
Hansen test
Ho: Instrumental variables are strictly exogenous
Model (1): ZScorc Model (2): ROA Model (3): ROE chi2(ll) 15.01 chi2(ll) 14.77 chi2(ll) 15.9
Prob > chi2 0.241 Prob > chi2 0.255 Prob > chi2 0.196
The Hansen test results indicate that the null hypothesis (Ho) is accepted across all models, confirming that the instrumental variables are strictly exogenous Consequently, this validates the exogeneity requirement for the instrumental variables, ensuring that the estimates derived from the two-step SGMM regression are consistent and unbiased.
CONCLUSION AND RECOMMENDATION
Conclusion
This study aligns with previous research, demonstrating that digital transformation and ICT applications significantly benefit the banking sector, particularly in Vietnam, by increasing profits, reducing risks, and enhancing stability for sustainable growth A focused investment in ICT at the national level is essential, as it fosters a stable development environment for banks operating within a unique legal framework linked to the nation’s economic health, thereby minimizing bank failures Although digital transformation requires substantial initial investments with delayed returns, its long-term value is evident Successful case studies reveal that pioneering banks leveraging specific digital products and flexible technology platforms gain a competitive edge in the evolving market Mastering ICT applications not only unlocks considerable profit potential but also drives organizational transformation, facilitating market share expansion and robust development.
This study not only reaffirms previous findings on the application of Information and Communication Technology (ICT) in the Vietnamese banking sector but also addresses critical gaps in the literature Utilizing the Generalized Method of Moments (GMM) regression enhances the reliability of the results By exploring both micro and macro factors, the research expands its analytical scope, considering individual bank dynamics alongside broader ICT trends in Vietnam Additionally, it highlights two essential dimensions—profitability and risk—offering a balanced evaluation of ICT's impact on the banking sector This comprehensive approach contributes to understanding how ICT fosters sustainable development within the industry.
This study significantly enhances our understanding of the impact of ICT on the Vietnamese banking industry, confirming the positive effects of ICT adoption while exploring new dimensions By integrating firm-level data with macroeconomic factors, it reveals how ICT drives profitability, mitigates risk, and promotes sustainable growth The inclusion of both bank-specific and national ICT factors paves the way for future research into technology's nuanced roles in financial markets Furthermore, the robust GMM regression analysis establishes a solid foundation for examining the long-term effects of ICT-driven transformation in the Vietnamese banking sector.
Limitations
While this study effectively fills significant research gaps in the current literature, the authors acknowledge certain limitations that open avenues for future research These constraints offer valuable chances to deepen our understanding of the complex relationship between Information and Communication Technology (ICT) and the Vietnamese banking sector.
Limited data availability is a significant challenge, as the study relies on information from the Ministry of Information and Communications covering only 2009 to 2020 This narrow timeframe hinders a thorough analysis of the rapidly changing ICT landscape and its effects on the banking sector Future research should aim to overcome this limitation by incorporating more recent data sets, particularly those from the transformative years post-2020 By doing so, we can gain a deeper understanding of the ongoing ICT revolution in Vietnamese banking.
The study's examination of the Vietnamese banking industry offers valuable insights, but its findings may not be universally applicable due to Vietnam's unique regulatory environment, economic structure, and cultural context To enhance the generalizability of the results, it is essential to broaden the research scope to include data from various emerging and developed economies worldwide This comparative analysis could uncover universal trends and highlight culturally-specific nuances in the relationship between information and communication technology (ICT) and banking, thereby deepening our understanding of this complex global phenomenon.
The study's model fails to consider the influence of unforeseen "black swan" events, such as the COVID-19 pandemic, underscoring the necessity for future research to adopt comprehensive frameworks that address these unpredictable disruptions By incorporating black swan variables into analyses, we can enhance our understanding of the resilience and adaptability of ICT-driven transformations during unexpected crises This insight is crucial for equipping the banking sector to tackle future challenges and maintain long-term sustainability.
In summary, this study has significantly enhanced our understanding of the role of ICT in the Vietnamese banking sector, yet its limitations highlight important opportunities for future research By overcoming data constraints, broadening the research scope, and including black swan variables, subsequent studies can further develop this groundwork and gain deeper insights into this dynamic and continuously evolving field.
Recommendations
Vietnamese banks face significant challenges in their digital transformation journey, primarily due to the absence of a comprehensive national citizen identification database and an effective e-KYC mechanism, which complicates online customer verification and secure transactions To overcome these obstacles, the State Bank of Vietnam (SBV) needs to develop regulations that are specifically tailored to the local context, promoting an environment that encourages the widespread adoption of information and communication technology (ICT) within the banking sector.
Cybersecurity poses a significant challenge for Vietnamese banks, as even advanced economies struggle to find effective online security solutions To enhance their defenses, banks must invest in updating their internal networks and deploying state-of-the-art ICT security software Regular customer education on online scams and phishing attempts is essential, alongside strengthening the ICT department and sales staff Ongoing training for ICT personnel is necessary to keep pace with technological advancements, while sales staff must be equipped to navigate the complexities of ICT-driven banking products and services.
The advancement of ICT infrastructure is essential for Vietnamese banks to fully realize digital transformation and improve stability By enhancing operational efficiency, banks can increase their total assets, allowing for greater investment in modernizing banking experiences, reducing costs, and boosting profitability Collaborating with Fintech companies, telecommunications firms, and ICT experts can create valuable synergies that enrich product offerings and enhance user convenience while minimizing redundant efforts Additionally, leveraging social media and online services is vital for sustainable growth, as these platforms provide high user traffic and a cost-effective means to reach a wider customer base By strategically utilizing these channels, banks can effectively promote their digital products and services, fostering greater adoption and driving success in the digital landscape.
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1 Data setting panel variable: ID (unbalanced) time variable: Year, 2009 to 2020 delta: 1 unit
2 Two-step SysGMM regression results and related tests 2.1 Model 1 - Zscore
Favoring space over speed To switch, type or click on mata: mata set matafavor speed, perm. Dynamic panel-data estimation, two-step system w
Group variable: ID Number of obs = 203
Time variable : Year Number of groups = 26
Number of instruments = 25 Obs per group: min = 3
ZScore Coef std Err t p>|t| [95% Conf Interval]
Warning: Uncorrected two-step standard errors are unreliable.
Instruments for orthogonal deviations equation
FOO.(ICTIndex ETA SIZE LLP GDP INF ATM Domesticcredit Fixedbroadband
GM-type (missing-0, separate instruments for each period unless collapsed)
ICTlndex ETA SIZE LLP GDP INF ATM Domesticcredit Fixedbroadband
GM-type (mỉssỉng=0, separate instruments for each period unless collapsed)
Arellano-Bond test for AR(1) in first differences: z = 0.84 Pr > 2 - 0.400
Arellano-Bond test for AR(2) in first differences: z = -0.77 Pr > z = 0.439
Sargan test of overid restrictions: chi2(12) = 25.41 Prob > chi2 = 0.013
(Not robust, but not weakened by many instruments.)
Hansen test of overid restrictions: chi2(12) = 15.01 Prob > chi2 = 0.241
(Robust, but can be weakened by many instruments.)
Difference-in-Hansen tests of exogeneity of instrument subsets:
Hansen test excluding group: chi2(ll) = 8.82 Prob > chi2 = 0.638
Difference (null H = exogenous): chi2(l) = 6.19 Prob > Chi2 = 0.013 gmm(ICTIndex, collapse lag(l ))
Hansen test excluding group: chi2(0) = 0.00 Prob > chi2 =
Difference (null H = exogenous): chi2(12) = 15.01 Prob > chi2 - 0.241 iv(ICTIndex ETA SIZE LLP GDP INF ATM Domesticcredit Fixedbroadband Fixedtelephone Internet Hansen test excluding group: chi2(0) = 0.00 Prob > chi2 =
Difference (null H = exogenous): chi2(12) = 15.01 Prob > chi2 = 0.241
Warning: unconnected two-step standand ennons ane unreliable.
Dynamic panel-data estimation,, two-step system ( iMM
Number of obs = Number of groups = Obs per group: min = avg = max =
203 26 3 7.81 12 ROA Coef std Err t p>|t| (95% Conf Interval]
Instruments for orthogonal deviations equation
FOO.(lCTlndex ETA SIZE LLP GOP INF ATM Domesticcredit Flxedbroadband
GMM-type (missing=0, separate instruments for each period unless collapsed)
ICTlndex ETA SIZE LLP GDP INF ATM Domesticcredit Fixedbroadband
GMM-type (missing-0, separate instruments for each period unless collapsed)
Arellano-Bond test for AR(1) in first differences: z = -1.74 Pr > z = 0.082
Arellano-Bond test for AR(2) In first differences: z - 1.09 Pr > z * 0.277
Sargan test of overid restrictions: Chi2(12) - 92.72 Prob > Chi2 = 0.000
(Not robust, but not weakened by many instruments.)
Hansen test of overid restrictions: Chl2(12) = 14.77 Prob > Chi2 = 0.255
(Robust, but can be weakened by many instruments.)
Difference-in-Hansen tests of exogeneity of instrument subsets:
Hansen test excluding group: chi2(ll) = 14.76 Prob > chi2 ■ 0.194
Difference (null H = exogenous): chi2(l) = 0.00 Prob > chỉ2 = 0.972 gmm(ICTIndex, collapse lag(l ))
Hansen test excluding group: chi2(0) = 0.00 Prob > ch!2 =
Difference (null H - exogenous): Chi2(12) - 14.77 Prob > chi2 - 0.255 iv(ICTIndex ETA SIZE LLP GDP INF ATM Domesticcredit Fixedbroadband Fixedtelephone Internet Mobile) Hansen test excluding group: Chl2(0) = 0.00 Prob > Chl2 =
Difference (null H = exogenous): chi2(12) = 14.77 Prob > chi2 = 0.255
Dynamic panel-data estimation, two-step system GW
Group variable: ID Number of obs = 203
Time variable : Year Number of groups - 26
Number of instruments = 25 Obs per group: min = 3
Warning: Unconnected two-step standard errors are unreliable.
ROE coef std Err t p>|t| [95% Conf Interval]
Instruments for orthogonal deviations equation
FOD.(ICTIndex ETA SIZE LLP GDP INF ATM Domesticcredit Fixedbroadband
GMM-type (Bissing-O, separate instruments for each period unless collapsed) l(l/.).ICTlndex collapsed
ICTIndex ETA SIZE LLP GDP INF ATM Domesticcredit Fixedbroadband
GMM-type (Bisslng-0, separate instruments for each period unless collapsed)
Arellano-Bond test for AR(1) in first differences: z - -1.91 Pr > z - 0.057
Arellano-Bond test for AR(2) in first differences: z = 0.95 Pr > z = 0.345
Sargan test of overid restrictions: chi2(12) = 111.39 Prob > chi2 = 0.000
(Not robust, but not weakened by many instruments.)
Hansen test of overid restrictions: chi2(12) - 15.90 Prob > chi2 - 0.196
(Robust, but can be weakened by many instruments.)
Difference-in-Hansen tests of exogeneity of instrument subsets:
Hansen test excluding group: Chi2(ll) - 15.35 Prob > Chl2 - 0.167
Difference (null H = exogenous): chi2(l) = 0.55 Prob > chi2 ■ 0.457 gmm(lCTlndex, collapse lag(l ))
Hansen test excluding group: chi2(0) - 0.00 Prob > chi2 -
Difference (null H = exogenous): chi2(12) = 15.90 Prob > chi2 = 0.196 lv(iCTindcx ETA SIZE LLP GOP INF ATM Oomesticcredit Fixedbroadband Fixedtelephonc Internet Mobile) Hansen test excluding group: chi2(0) = 0.00 Prob > chi2 -
Difference (null H = exogenous): chi2(12) = 15.90 Prob > chi2 = 0.196
Variable Obs Mean std Dev Min Max