Digital Finance Infrastructure and Growth of Commercial Banking Firms in Nigeria

Digital Finance Infrastructure and Growth of Commercial Banking Firms in Nigeria | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Digital Finance Infrastructure and Growth of Commercial Banking Firms in Nigeria Marshal Iwedi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4051890/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study delves into the intricate relationship between digital finance infrastructure and the growth of commercial banking firms in Nigeria. Through a comprehensive analysis of various financial indicators and statistical tests, we offer critical insights into the dynamics of the Nigerian banking sector. The findings reveal a resilient and steadily growing banking industry, even in the face of economic challenges and the global COVID-19 pandemic. Key highlights include the exponential rise in digital infrastructure, exemplified by the proliferation of Automated Teller Machines (ATMs), Point of Sale (POS) machines, and web banking accounts. These digital channels have significantly influenced the accessibility and convenience of banking services in Nigeria. Our analysis employs correlation, regression, and Granger causality tests to explore the intricate relationships between bank total assets and digital infrastructure components. While positive correlations between bank total assets and digital infrastructure components suggest a strong link between technological expansion and banking growth, the analysis reveals nuanced relationships. Particularly, the unexpected negative impact of ATMs on bank total assets warrants further investigation. The decline in the number of POS machines in 2022 poses questions about the factors contributing to this trend. Furthermore, while web banking accounts have grown significantly, their influence on bank total assets remains limited. Our findings emphasize the paramount importance of continued investments in digital finance infrastructure for the Nigerian banking sector's growth. However, they also underscore the need for a more profound understanding of the underlying drivers of these trends. This study offers valuable insights for policymakers, financial institutions, and researchers interested in fostering financial inclusion and optimizing digital banking services in Nigeria's ever-evolving financial landscape. Finance Digital Finance Infrastructure Banking Growth Nigerian Banking Sector Point of Sale Machines (POS) Web Banking Impact Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction In recent years, the global financial landscape has witnessed an unprecedented transformation, marked by the rapid integration of digital technologies into traditional banking systems. This paradigm shift has been particularly pronounced in emerging economies, where digital finance infrastructure has emerged as a powerful catalyst for economic growth and financial inclusion. Nigeria, as one of Africa's largest economies, stands at the forefront of this transformative wave, with its banking sector experiencing significant evolution driven by digital finance initiatives. As the backbone of any economy, the banking sector plays a pivotal role in channeling financial resources, facilitating investment, and driving economic expansion [4]. The infusion of digital technologies has redefined the traditional paradigms of banking, fostering innovation, efficiency, and accessibility [9]. The proliferation of mobile banking, electronic payments, blockchain technologies, and fintech collaborations has not only revolutionized customer experiences but has also fundamentally altered the competitive landscape for banking firms operating in Nigeria [3]. In this dynamic environment, safety and the quality of service delivery have supplanted traditional concerns about banking institutions. Customers, now more discerning and vigilant due to past incidents of distressed banks, scrutinize the level of professionalism and service efficiency before entrusting their funds. In response, banks have come to realize that the cornerstone of providing quality services lies in the adoption of digital infrastructure and technology. Consequently, Nigerian banks have made substantial investments in technology, transitioning their operations from manual to automated systems in recent years [6]. [3] aptly noted that in the 21st century, global banks must undertake comprehensive overhauls of their operations, payment systems, and delivery mechanisms to thrive in the new millennium. This imperative arises from the pressures of globalization, consolidation, deregulation, and the rapid evolution of technology. Unlike the past, when ledger cards were the norm, contemporary banking is now seamlessly integrated into the cloud, enabling inter-branch and inter-bank transactions. The advent of mobile telephony in 2000, coupled with enhanced access to personal computers and internet services, has further accelerated the growth of digital banking in Nigeria. Moreover, many banks have established sophisticated computer interconnectivity frameworks that facilitate the seamless exchange of data and multimedia across intranets, extranets, and the worldwide web. Additionally, they have prioritized staff computer literacy, equipping them with the skills to effectively locate, analyze, store, and utilize information for data-driven decision-making. [7] underscored the pivotal role of technology in enabling new generation banks to deliver efficient, real-time services, thereby enabling customers to make withdrawals from any branch across the country. While the traditional mode of banking has persisted for a considerable period, it is beset with challenges including security concerns, lack of personalization, limited service accessibility, time inefficiencies, and customer inconvenience. However, the introduction of digital finance infrastructure has revolutionized banking practices. Queuing in banks has been minimized, transaction validity for international dealings is virtually instantaneous, and the process is streamlined, eliminating the need for copious documentation and physical presence at bank desks. Notably, [5] highlights that the introduction of digital finance infrastructure has substantially augmented banking firms' deposit base. This technological leap has fundamentally altered the modus operandi of Nigerian banks, shifting towards a digital-centric operational model. The integration of digital banking not only enhances the efficiency of banking services but also augments the overall banking experience. In light of these significant advancements and the potential to bridge existing gaps in knowledge and literature, this study seeks to comprehensively examine the impact of digital finance infrastructure on the growth trajectory of banking firms in Nigeria. 2. Literature Review 2.1 The Concept of Digital Finance Infrastructure Digital finance infrastructure is the integrated network of technological and organizational elements that facilitate the delivery and operation of financial services through digital means. It encompasses the hardware, software, networks, protocols, and regulatory frameworks that enable the seamless execution of various financial transactions, including payments, transfers, investments, and other financial activities, using digital channels such as mobile devices, computers, and the internet [6]. This infrastructure enables individuals, businesses, and institutions to access, manage, and conduct financial transactions electronically, often without the need for physical presence at a brick-and-mortar financial institution. It encompasses a wide range of components, including automated teller machines (ATMs), point-of-sale (POS) terminals, web payment platforms, mobile banking apps, secure communication protocols, digital wallets, and back-end banking systems [3]. Additionally, it involves compliance with relevant regulations and cybersecurity measures to ensure the security and integrity of financial transactions. The ultimate goal of a robust digital finance infrastructure is to enhance financial inclusion, accessibility, efficiency, and security in the delivery of financial services, contributing to economic development and empowering individuals and businesses to participate more actively in the financial ecosystem. The key components of digital finance infrastructure in Nigeria: ATMs (Automated Teller Machines): ATMs are electronic devices that allow customers to perform basic banking transactions without the need for a bank teller. They provide self-service options for activities like cash withdrawals, balance inquiries, fund transfers, and more. These machines are typically available 24/7 in public locations like shopping malls, airports, and street corners [11]. ATMs use a combination of hardware and software components. They have card readers to read debit or credit cards, PIN pads for user authentication, a display screen for interaction, a cash dispenser, and sometimes a printer for receipts. Internally, they are equipped with a computer, network connections, and security measures.ATMs communicate with the customer's bank over a secure network. When a customer inserts their card and enters their PIN, the ATM connects to the bank's servers to verify the user's identity and process the requested transaction.ATMs use various security features including encryption to protect user data, cameras for surveillance, and physical security measures to prevent tampering. POS (Point of Sale) Technology: POS technology refers to the hardware and software used at the point where a customer makes a payment to a merchant in exchange for goods or services. It includes a computerized system that allows businesses to process sales, manage inventory, and generate reports. It's used in retail and other businesses to process payments [8]. A POS system includes hardware components like a cash register, barcode scanner, card reader, and receipt printer. It also requires software to manage sales, inventory, and process payments. When a customer makes a purchase, the merchant uses the POS system to scan or input the items being purchased. The system calculates the total amount, and the customer can then make the payment using various methods like credit/debit cards, mobile wallets, or even cash. POS systems are usually connected to a network, allowing them to communicate with the merchant's bank to authorize and complete the transaction. Web Banking Technology: Web banking technology, also known as online banking, enables customers to access their bank accounts and perform financial transactions through the internet. This includes activities like checking account balances, transferring funds, paying bills, and even applying for loans or opening new accounts [12]. Online banking platforms are secured by encryption and authentication protocols to ensure the safety of user information. Web banking relies on internet technologies, including web servers, databases, and secure communication protocols (such as HTTPS), to provide a secure and user-friendly interface for customers to interact with their accounts. Customers log in to a secure website provided by their bank. Once logged in, they can view account balances, transfer funds between accounts, pay bills, and perform other banking activities online. Web banking employs various security measures including encryption to protect user data, multi-factor authentication for user verification, and regular security updates to safeguard against threats. 2.2 Theoretical Framework The study is grounded in both the Technology Acceptance Model (TAM) and the Innovation Diffusion Theory. These theoretical frameworks provide the foundation for understanding the adoption and diffusion of digital finance innovations in the context of the research. TAM focuses on how individuals perceive and accept new technologies, while the Innovation Diffusion Theory explains how innovations spread within social systems over time. By combining these theories, the study aims to comprehensively analyze the factors influencing the adoption and proliferation of digital finance services, considering both individual user perceptions and broader societal diffusion patterns. This dual theoretical underpinning enhances the study's analytical depth and provides a holistic framework for investigating the adoption of digital finance technologies. 2.3 Empirical Review In recent years, several studies have delved into the relationship between digital finance infrastructure and the performance of banking firms. Noteworthy contributions include [2] examination of digital banking and deposit money bank performance in Nigeria. This study, spanning from 2010 to 2018, utilized net interest margin as a proxy for bank performance, with ATM, POS, mobile banking, and web pay serving as proxies for digital banking. Interestingly, Deekor found that while ATM, POS, and web pay showed no significant effect on net interest margin, mobile banking exhibited a positive and substantial relationship with this metric. Similarly, [12] conducted a comprehensive analysis using secondary data from Central Bank of Nigeria's Statistical Bulletin and Financial Stability Reports. They investigated the link between digital banking and the profitability of deposit money banks in Nigeria for the period of 2010 to 2018. The study used ATMTV, POSTV, MBTV, and IBTV to proxy digital banking, and ROA to proxy commercial bank performance. The results demonstrated that ATMTV and POSTV each had a positive relationship with ROA, while both MBTV and IBTV showed a negative relationship. This implies that, individually, digital banking channels had no significant effect on bank performance during the period under study. In a more recent contribution, [1] proposed a novel mechanism through which technology-based banking services stimulate bank deposit growth. Employing ARDL bounds-testing and Granger causality approach, the study examined short-run, long-run, and causal relationships among variables from 2006 Q1 to 2019 Q4. The results indicated a significant positive relationship between the number of ATMs, value of POS transactions, and total bank deposits in Nigeria, both in the short run and long run. On the other hand, mobile and internet banking were found to have a negative and insignificant impact, suggesting low penetration of these services in Nigeria. Notably, only the number of ATMs was identified to have a causal influence on bank deposits, emphasizing the importance of continuous ATM deployment. 3. Methodology The research design for this study follows a quantitative approach, employing mathematical, statistical, and numerical analysis of data to establish relationships among measured variables. The study utilized secondary data, which consists of a combination of published and unpublished materials relevant to the research objectives. Secondary data is considered significant as it forms the logical framework of the research. The collected secondary data includes Central Bank of Nigeria periodic reports and total asset reports of commercial banks spanning the period 2009-2022. Upon collection, the data underwent a comprehensive cleaning process, including sorting and checking for completeness and consistency. This step ensures the reliability and accuracy of the data before further analysis. Statistical Package for the Social Sciences (SPSS) was employed to conduct descriptive statistical analyses, such as maximum, minimum, mean, and standard deviation. These analyses aimed to outline sample characteristics and identify significant trends within the collected data. A multiple linear regression model was chosen to estimate the relationships between the variables under investigation. The regression model is designed to explore the relationship between digital finance infrastructure and the growth of banking firms through the use of digital finance technology. The variables considered in the model include the number of automated teller machines (ATM), volume of web banking transactions (WEB), and the volume of point of sales technology transactions (POS). The constant term (α0) represents the baseline value. The model aims to provide insights into the impact of these digital finance technologies on the deposit base of banking firms. The regression model is specified as follows: 4. Results and Interpretations 4.2 Trend Analysis of Digital Finance Infrastructure and Growth of Banking Firms in Nigeria The data presented in Figure 4.1 illustrates the total assets of commercial banks in Nigeria spanning from 2009 to the projected year 2022. Notably, certain quarters exhibit gaps in reported values, either due to data unavailability or a lack of reporting for those specific periods. In this analysis, we aim to meticulously examine the accessible data and derive meaningful insights. The dataset encapsulates the total assets of commercial banks in Nigeria over a 13-year timeframe, segmented by year and quarter. It's crucial to acknowledge the existence of data gaps, wherein numerous quarters lack reported values—potentially stemming from unavailable data or non-reporting during those specific periods. To facilitate a meaningful analysis, our focus will initially hone in on the available data points and their discernible trends. 2009 to 2012: Witnessing a consistent upswing in total assets during this phase, the figures ascend from 17,522.86 in Q1 2009 to 21,288.14 in Q1 2012, indicating a sustained growth trajectory. 2013 to 2015: This trend persists, with total assets reaching 28,173.26 in Q1 2015. 2016 to 2019: Marked by another substantial growth period, the total assets nearly double from 31,682.82 in Q1 2016 to 42,523.85 in Q1 2019. However, a dip is discernible in Q1 2020, plummeting to 37,298.41. An abrupt surge in Q1 2021 to 57,429.38 implies a potential rebound post the 2020 downturn. Regrettably, data for the remaining quarters of 2021 and the entirety of 2022 is absent, posing challenges in evaluating the overall trend for these years. Several variables could impact the observed trends in commercial bank total assets in Nigeria. The broader economic landscape, encompassing GDP growth, inflation rates, and government policies, holds sway over commercial banks' performance. The Central Bank of Nigeria's monetary policies, including interest rates and reserve requirements, exert influence on the lending and investment activities of commercial banks. Alterations in banking regulations and prudential standards can reshape the balance sheets of commercial banks. Global economic events, such as the 2008 financial crisis and the COVID-19 pandemic, wield substantial influence on the financial sector. While the available data delineates a general upward trajectory in commercial bank total assets in Nigeria over the past decade, it is imperative to factor in the absent data and external influences when formulating conclusions or decisions based on this information. The data presented in Figure 4.2 illustrates the total count of Automated Teller Machines (ATMs) in Nigeria spanning a 14-year period, categorized by both year and quarter. This dataset unveils notable variations in the total number of ATMs throughout the years, prompting a critical examination of the underlying reasons for these fluctuations and their potential implications for the banking industry. Commencing from Q1 2009, the number of ATMs in Nigeria witnessed a steady rise, escalating from 26,103,489 to 95,277,416 by Q4 2011, indicative of a burgeoning demand for ATM services during this period. Although a minor dip occurred in Q1 2012, subsequent quarters experienced a rebound, maintaining an overall positive trend that signifies sustained demand for ATM services. In 2013, the count of ATMs remained relatively constant, suggesting a potential plateau in ATM deployment. However, a substantial surge transpired, with the number peaking at 116,870,000 in Q4 2015, potentially driven by banks expanding their ATM networks to cater to an expanding customer base. A remarkable escalation unfolded in the following years, exceeding 239 million ATMs in Q4 2017, possibly linked to an increased focus on financial inclusion and technology-driven banking services. Despite a continued increase in 2018, the pace slowed, hinting at a probable saturation point in ATM deployment. 2019 saw a decline in the number of ATMs, possibly indicative of shifts in banking strategies or a preference for alternative digital banking channels. Notably, a surge in Q1 and Q3 2020 aligns with the onset of the COVID-19 pandemic, suggesting heightened demand for cash withdrawal and reduced reliance on in-branch banking. The data takes an unexpected turn in Q1 2022, depicting a substantial and uniform surge in the number of ATMs across all quarters. Such an abrupt and significant increase raises concerns about potential anomalies or errors in the data, necessitating a thorough investigation to validate its accuracy. Considering the broader context, economic growth may fuel increased demand for banking services, including ATMs. Government policies promoting financial inclusion and cashless transactions can influence ATM network growth. The evolution of banking technologies, such as mobile banking, may impact the necessity for physical ATMs. Events like the COVID-19 pandemic can alter banking behavior, with a surge in ATM usage for cash withdrawal during lockdowns. Given the extraordinary increase in ATMs in Q1 2022, it is imperative to scrutinize and validate this data for accuracy. Understanding the dynamics behind the observed trends is crucial for making informed decisions within the banking and financial sector. The data depicted in Figure 4.3 outlines the 14-year trajectory of Point of Sale (POS) machines in Nigeria, segmented by year and quarter. This information is pivotal for comprehending the evolution of digital finance infrastructure and its influence on the expansion of banking enterprises within Nigeria. Notably, Figure 4.3 illustrates a noteworthy surge in the quantity of POS machines from 2009 to 2022, underlining their critical role in enabling electronic transactions. Over this period, the number of POS machines exhibited a steady rise, with a pronounced peak in Q4 2012, indicating an escalating adoption of electronic payment methods. Subsequently, there was a substantial surge in POS machines, particularly from 2013 onward, demonstrating an increasing reliance on electronic payment systems. The figures more than doubled during this phase, suggesting a robust trend towards electronic transactions. Noteworthy growth persisted from 2016 to 2019, aligning with the global trend of digitalization in the financial sector. A remarkable upswing was observed in the first and fourth quarters of 2020, potentially linked to the COVID-19 pandemic, expediting the shift to contactless payments and diminishing cash usage. However, the data reveals an unprecedented surge in Q1 2021, with a consistent number of POS machines reported for all quarters of 2022. This raises concerns about potential data anomalies or errors, necessitating further investigation to verify data accuracy. The proliferation of POS machines in Nigeria holds multifaceted implications for banking firms and the broader digital finance infrastructure. A higher number of POS machines translates to increased electronic payment options for customers, fostering elevated satisfaction and retention rates for banking institutions. The expansion of POS networks contributes to financial inclusion by extending access to digital payment methods across a broader demographic. Additionally, the growth of POS machines diminishes reliance on cash transactions, enhancing security and transparency in the financial system. Banking entities stand to generate revenue through transaction fees and service charges associated with POS usage. Figure 4.4 presents a comprehensive overview of the total number of web banking account holders in Nigeria spanning a 14-year period, segmented by year and quarter. This dataset is indispensable for comprehending the evolution of digital finance infrastructure and its consequential impact on the expansion of banking institutions in Nigeria. The data discloses a substantial upswing in the count of web banking account holders from 2009 to 2022. These accounts constitute a pivotal component of the digital finance framework, facilitating online access to banking services. Noteworthy spikes are evident in Q3 2009 and Q1 2012, indicating an early embrace of web banking services in Nigeria. The momentum persists, with a remarkable surge in Q3 2015, aligning with the global trend toward digital banking. From 2016 to 2019, consistent growth prevails, signaling a heightened demand for web banking services and a surge in digital financial transactions. The unprecedented spike across all quarters of 2020 can be attributed to the COVID-19 pandemic, hastening the adoption of digital banking due to social distancing measures and lockdowns. Q1 2022 reveals an extraordinary and uniform increase in web banking account holders, potentially signaling data anomalies or errors, necessitating further investigation for data accuracy confirmation. The proliferation of web banking account holders holds multifaceted implications for banking institutions and the digital finance landscape. Increased customer engagement fosters stronger bank-customer relationships, while the cost-effectiveness of digital transactions enhances bank profitability. Furthermore, the expansion of web banking services contributes to financial inclusion by broadening access to banking services. However, caution is warranted as the significant and uniform surge in Q1 2022 and throughout 2022 may introduce distortions in data analysis and interpretation. Consequently, a thorough investigation is imperative to elucidate the underlying dynamics of these trends and ensure data accuracy. 4.2 Descriptive Result Table 4.1 Descriptive Result digital finance infrastructure and growth of banking firms BTA ATM POS WEB Mean 33016.68 2.84E+09 1.44E+08 4.36E+08 Median 29928.04 1.21E+08 11058740 2693216. Maximum 65459.46 3.77E+10 9.71E+08 3.52E+09 Minimum 17331.56 7762869. 590.6460 289326.0 Std. Dev. 14070.45 9.75E+09 2.83E+08 9.85E+08 Skewness 0.976836 3.327308 2.155988 2.365449 Kurtosis 3.118663 12.07327 6.197182 7.405985 Jarque-Bera 8.938806 295.4192 67.23526 97.51957 Probability 0.011454 0.000000 0.000000 0.000000 Sum 1848934. 1.59E+11 8.06E+09 2.44E+10 Sum Sq. Dev. 1.09E+10 5.23E+21 4.40E+18 5.34E+19 Observations 56 56 56 56 Source : E-view 9.0 output The descriptive statistics presented in Table 4.1 shed light on the digital finance infrastructure and the growth of banking firms in Nigeria, focusing on key variables: Bank Total Assets (BTA), Total number of Automated Teller Machines (ATM), Total number of Point of Sale Machines (POS), and Total number of holders of Web banking accounts (WEB). The mean, representing the average value across observations, and the median, indicating the middle value in ascending order, provide insights. BTA's mean is approximately 33,016.68, exceeding the median (29,928.04), implying larger banks with notably higher assets. For ATM, POS, and WEB, the means surpass the medians, signaling a positive skewness caused by a few high-value observations. Maximum values denote the dataset's peaks, while minimum values represent the lows. BTA's maximum is around 65,459.46, showcasing a bank with substantial assets, while ATM's maximum is 3.77E+10, significantly higher than mean and median. POS's maximum (9.71E+08) and WEB's maximum (3.52E+09) highlight extensive machine and account holder numbers. Standard deviations, indicating data spread, are sizable, implying significant variability across banks. Positive skewness for all variables reveals right-skewed distributions with longer tails on the right side, indicating banks with exceptionally high values. High kurtosis suggests heavy tails and more extreme values compared to a normal distribution. The Jarque-Bera test, assessing normality, yields low p-values for all variables, reinforcing non-normal, right-skewed, and heavy-tailed distributions. These values provide overall magnitude and variability insights. This analysis uncovers substantial variations in digital finance infrastructure among Nigerian banks. [10] emphasizes embracing digital innovations for digitally-savvy customers, while [5] identifies hindering factors like inadequate infrastructure and government regulations. Positive skewness and high kurtosis hint at banks with exceptionally high digital finance infrastructure values, potentially impacting overall banking growth. Table 4.1's descriptive statistics offer valuable insights, suggesting further analysis to explore factors influencing these variations would be beneficial. 4.3 Stationarity Test Result Table 4.2 Unit Root Test for digital finance infrastructure and growth of banking firms D(BTA) D(ATM) D(POS) D(WEB) ADF Statistics -7.808302 -5.832509 -6.652185 -6.280935 1% -3.557472 -3.508508 -3.588509 -3.571310 5% -2.916566 -3.184230 -2.929734 -2.922449 Probability 0.0000 0.0000 0.0000 0.0000 Source: Extracted from E-view 9.0 Output In Table 4.2, we present the outcomes of a unit root test conducted on variables associated with digital finance infrastructure and the growth of banking firms in Nigeria. The Augmented Dickey-Fuller (ADF) test statistics, critical values at 1% and 5% significance levels, and p-values are detailed for Bank Total Assets (BTA), Total Automated Teller Machines (ATM), Total Point of Sale Machines (POS), and Total Web Banking Accounts (WEB). The primary aim of this test is to ascertain whether these variables exhibit stationarity or non-stationarity. The ADF statistics exhibit highly negative values across all four variables, ranging approximately from -5.83 to -7.81. These negative values signify that the variables have undergone differencing (hence the "D" prefix), a common technique to transform non-stationary time series data into stationary form. Critical values serve as thresholds to assess the statistical significance of the ADF statistics. In this instance, critical values at 1% and 5% significance levels are provided. For all four variables, the ADF statistics surpass the critical values at both significance levels, indicating statistical significance and implying that the variables are stationary. P-values are supplied to gauge the statistical significance of the ADF statistics, with lower p-values indicating higher statistical significance. Remarkably, all four variables report p-values as 0.0000, suggesting that the ADF statistics are highly statistically significant, providing robust evidence against the null hypothesis positing non-stationarity. The unit root test results affirm that variables related to digital finance infrastructure (BTA, ATM, POS, WEB) and the growth of banking firms in Nigeria have undergone differencing, rendering them stationary. Stationarity is pivotal in time series analysis as it ensures that key statistical properties, such as mean and variance, remain constant over time. Stationary data is more amenable to modeling and analysis. The findings in Table 4.2 offer compelling evidence that these variables in the context of the Nigerian banking sector are stationary, a critical foundation for robust time series analysis. However, further exploration is warranted to delve into the relationships and potential causal factors underlying these variables within the Nigerian banking landscape. 4.4 Co-integration Test Table 4.3 Unrestricted Cointegration Rank Test (Trace) Hypothesized No. of CE(s) Eigenvalue Trace Statistic 0.05 Critical Value Prob.** None * 0.858799 149.8008 47.85613 0.0000 At most 1 * 0.518034 44.09211 29.79707 0.0006 At most 2 0.076883 4.678500 15.49471 0.8420 At most 3 0.006618 0.358550 3.841466 0.5493 Trace test indicates 2 cointegrating eqn(s) at the 0.05 level * denotes rejection of the hypothesis at the 0.05 level **MacKinnon-Haug-Michelis (1999) p-values Source: Extracted from E-view 9.0 Output Table 4.3 outlines the Unrestricted Cointegration Rank Test (Trace) results for digital finance infrastructure and banking firms' growth in Nigeria. Cointegration, indicating a long-term relationship between variables, is explored across hypothesized numbers of cointegrating equations (CEs) from "None" to "At most 3." Eigenvalues signify cointegration strength, with larger values indicating stronger relationships. The Trace Statistic measures this strength for each hypothesized number of CEs, comparing it to the Critical Value at the 0.05 significance level. Under "None," the Trace Statistic (149.8008) significantly exceeds the critical value (47.85613), with a Prob. of 0.0000, signifying cointegrating relationships. For "At most 1," the Statistic (44.09211) surpasses the critical value (29.79707), with a Prob. of 0.0006, indicating at least one cointegrating relationship. However, for "At most 2" and "At most 3," the Trace Statistic drops below the critical value, yielding high probabilities and suggesting limited or no cointegrating relationships. This aligns with the notion of at least one cointegrating relationship, implying a long-term connection. This connection suggests a lasting equilibrium influenced by economic or structural factors, not implying causality. [9] notes cointegration's ability to identify common stochastic trends among financial variables. Results indicate a long-term equilibrium between digital finance infrastructure and banking firms' growth, warranting further research for a comprehensive understanding of its nature and implications. Table 4.4 Unrestricted Cointegration Rank Test (Maximum Eigenvalue) Hypothesized No. of CE(s) Eigenvalue Max-Eigen Statistic 0.05 Critical Value Prob.** None * 0.858799 105.7086 27.58434 0.0000 At most 1 * 0.518034 39.41361 21.13162 0.0001 At most 2 0.076883 4.319950 14.26460 0.8241 At most 3 0.006618 0.358550 3.841466 0.5493 Max-eigenvalue test indicates 2 cointegrating eqn(s) at the 0.05 level * denotes rejection of the hypothesis at the 0.05 level **MacKinnon-Haug-Michelis (1999) p-values Source: Extracted from E-view 9.0 Output Table 4.4 presents the results of the Unrestricted Cointegration Rank Test (Maximum Eigenvalue) for digital finance infrastructure and banking firm growth in Nigeria. Hypothesized cointegrating relationships range from "None" to "At most 3." A significant Maximum Eigenvalue Statistic under "None" (105.7086 vs. 27.58434) suggests cointegrating relationships. "At most 1" also shows significance (39.41361 vs. 21.13162), implying at least one relationship. However, "At most 2" and "At most 3" lack significance, hinting at limited relationships. Results align with the Trace test, indicating at least one cointegrating relationship. This implies a lasting connection between digital finance infrastructure and banking growth in Nigeria, supported by studies. In summary, advancing digital finance infrastructure can enhance the efficiency and growth of banking firms in Nigeria. Further investigation is warranted to understand this relationship. 4.5 Regression Results Table 4.5 Regression Results of digital finance infrastructure and bank assets Variable Coefficient Std. Error t-Statistic Prob. C 26167.96 956.1897 27.36691 0.0000 ATM -3.70E-07 1.84E-07 -2.007864 0.0499 POS 5.45E-05 6.46E-06 8.437033 0.0000 WEB 1.18E-07 2.22E-06 0.053199 0.9578 R-squared 0.816712 Mean dependent var 33016.68 Adjusted R-squared 0.806138 S.D. dependent var 14070.45 S.E. of regression 6195.190 Akaike info criterion 20.36968 Sum squared resid 2.00E+09 Schwarz criterion 20.51435 Log likelihood -566.3511 Hannan-Quinn criter. 20.42577 F-statistic 77.23556 Durbin-Watson stat 1.841693 Prob(F-statistic) 0.000000 Source: Extracted from E-view 9.0 Output Table 4.5 presents the regression results of the relationship between digital finance infrastructure variables (ATM, POS, WEB) and Bank Total Assets (BTA) in Nigeria. Let's critically discuss these findings: Table 4.5 provides the coefficients for the intercept (C), ATM, POS, and WEB. The coefficient for the intercept (C) is 26167.96. This represents the estimated value of BTA when all other independent variables (ATM, POS, WEB) are equal to zero. The coefficients for ATM, POS, and WEB represent the estimated change in BTA for a one-unit change in each respective independent variable, holding other variables constant. ATM has a negative coefficient of -3.70E-07, indicating that an increase in the number of ATMs is associated with a decrease in BTA, although this relationship is not very strong. POS has a positive coefficient of 5.45E-05, indicating that an increase in the number of Point of Sale Machines is associated with an increase in BTA. This relationship appears to be strong. WEB has a very small positive coefficient of 1.18E-07, suggesting that the number of holders of Web banking accounts has a minimal impact on BTA. The R-squared value is 0.816712, indicating that approximately 81.67% of the variation in BTA can be explained by the independent variables (ATM, POS, WEB) in the regression model. This suggests a relatively good fit of the model. The Adjusted R-squared value is 0.806138, which is slightly lower than the R-squared value. This value accounts for the number of independent variables and penalizes the inclusion of unnecessary variables. It is still relatively high, indicating a good fit. The standard error of regression is 6195.190. It represents the average deviation of the observed values of BTA from the values predicted by the regression model. A lower standard error indicates a better fit of the model to the data. The F-statistic is 77.23556, and the associated p-value (Prob(F-statistic)) is reported as 0.000000, which is very close to zero. A low p-value for the F-statistic suggests that the overall model is statistically significant. In this case, it indicates that at least one of the independent variables (ATM, POS, WEB) is a statistically significant predictor of BTA. The Durbin-Watson statistic is 1.841693. This statistic measures the presence of autocorrelation in the residuals (errors) of the regression model. A value between 1 and 3 is often considered acceptable, and this value falls within that range, indicating that there may not be strong autocorrelation in the residuals. The regression results suggest that the number of Point of Sale Machines (POS) has a positive and statistically significant impact on Bank Total Assets (BTA). An increase in POS is associated with an increase in BTA. The number of Automated Teller Machines (ATM) also has an impact on BTA, but the relationship is negative and less significant. [11] found a negative but insignificant relationship between ATM transactions and return on equity in Nigerian deposit money banks. [5] also reported a negative impact of ATMs on the efficiency of Greek banks. However, [12] found that ATMs do not have any influence on the Return On Asset (ROA) of Japanese banks. These findings suggest that while there may be a negative relationship between the number of ATMs and Bank Total Asset, the significance of this relationship is not consistent across different countries and banking systems. The number of holders of Web banking accounts (WEB) does not appear to have a meaningful impact on BTA, as indicated by the very small and statistically insignificant coefficient. [1] found that internet banking had a negative and insignificant effect on banking performance, while size and capital had a positive and significant effect. Credit risk, expense management, and economic growth had a negative and significant effect on banking performance. [7] conducted a study in Bangladesh and found that banks with online banking had higher Return on Asset (ROA) and Return on Equity (ROE) compared to banks without online banking, but the results were insignificant. Additionally, ROA and ROE were lower after the implementation of internet banking, which could be attributed to initial infrastructure development costs and a failure to attract mass-scale adoption. [1] focused on First Bank Nigeria Plc and found that internet banking, including factors such as cheap internet costs, 24-hour internet services, and ICT competence of customers, significantly contributed to the bank's performance. The regression analysis in Table 4.5 provides insights into the relationships between digital finance infrastructure variables and Bank Total Assets in Nigeria. The findings highlight the importance of Point of Sale Machines (POS) in driving the growth of bank assets, while also noting the potential influence of Automated Teller Machines (ATM). The impact of Web banking account holders (WEB) appears to be negligible in this context. 4.6 Causality Test Table 4.6 Causality Test on the effect of Digital finance infrastructure on total bank assets Null Hypothesis: Obs F-Statistic Prob. ATM does not Granger Cause BTA 54 0.46367 0.6317 BTA does not Granger Cause ATM 3.97882 0.0250 POS does not Granger Cause BTA 54 0.17204 0.8425 BTA does not Granger Cause POS 2.79296 0.0710 WEB does not Granger Cause BTA 54 1.91985 0.1575 BTA does not Granger Cause WEB 4.80165 0.0125 POS does not Granger Cause ATM 54 52.9738 6.E-13 ATM does not Granger Cause POS 7.05835 0.0020 WEB does not Granger Cause ATM 54 1.54502 0.2235 ATM does not Granger Cause WEB 0.08798 0.9159 WEB does not Granger Cause POS 54 0.83824 0.4386 POS does not Granger Cause WEB 16.1276 4.E-06 Source: Extracted from E-view 9.0 Output Table 4.6 presents the results of causality tests conducted to examine the directional causality between digital finance infrastructure variables (ATM, POS, WEB) and Bank Total Assets (BTA) in Nigeria. Let's critically discuss these findings: The first test, examining whether ATM Granger Causes BTA, results in an observed F-Statistic of 0.46367 with a probability (Prob.) of 0.6317. This suggests that there is no strong evidence to reject the null hypothesis, implying that ATM does not significantly Granger Cause BTA. The second test, examining whether BTA Granger Causes ATM, results in an observed F-Statistic of 3.97882 with a probability (Prob.) of 0.0250. In this case, there is evidence to reject the null hypothesis, suggesting that BTA Granger Causes ATM. The first test, examining whether POS Granger Causes BTA, results in an observed F-Statistic of 0.17204 with a probability (Prob.) of 0.8425. This indicates that there is no strong evidence to reject the null hypothesis, suggesting that POS does not significantly Granger Cause BTA. The second test, examining whether BTA Granger Causes POS, results in an observed F-Statistic of 2.79296 with a probability (Prob.) of 0.0710. In this case, there is some evidence to reject the null hypothesis, suggesting that BTA might Granger Cause POS at a lower significance level (0.0710). The first test, examining whether WEB Granger Causes BTA, results in an observed F-Statistic of 1.91985 with a probability (Prob.) of 0.1575. This suggests that there is no strong evidence to reject the null hypothesis, implying that WEB does not significantly Granger Cause BTA. The second test, examining whether BTA Granger Causes WEB, results in an observed F-Statistic of 4.80165 with a probability (Prob.) of 0.0125. In this case, there is evidence to reject the null hypothesis, suggesting that BTA Granger Causes WEB. Granger causality tests aim to determine whether one variable can predict changes in another variable. The results suggest that while ATM and POS do not significantly Granger Cause BTA, BTA might Granger Cause ATM and POS at a lower significance level. For WEB, there is no strong evidence that it Granger Causes BTA, but BTA significantly Granger Causes WEB. The causality tests in Table 4.6 offer insights into the potential temporal relationships between digital finance infrastructure variables and Bank Total Assets in Nigeria. While ATM and POS do not seem to significantly Granger Cause BTA, there is some evidence to suggest that BTA might Granger Cause ATM and POS. For WEB, there is no strong evidence of Granger causality, but BTA significantly Granger Causes WEB. Further analysis is needed to explore the underlying mechanisms behind these temporal relationships. 5. Conclusion In conclusion, the regression analysis sheds light on the intricate relationships between digital finance infrastructure variables and Bank Total Assets (BTA) in Nigeria. The findings highlight the substantial impact of Point of Sale Machines (POS) on driving the growth of bank assets, indicating a robust and positive relationship. On the other hand, Automated Teller Machines (ATM) exhibit a weaker and negative association with BTA, although the significance varies across different studies and banking systems. The number of Web banking account holders (WEB) appears to have a negligible impact on BTA, as indicated by a small and statistically insignificant coefficient. The overall model demonstrates a commendable fit, explaining approximately 81.67% of the variation in BTA through the independent variables. This suggests that the included digital finance infrastructure variables contribute significantly to understanding the dynamics of bank asset growth in the Nigerian context. Based on these findings, the following recommendations are offered: Emphasize Point of Sale (POS) Infrastructure: Given the positive and significant impact of POS on Bank Total Assets, financial institutions in Nigeria may consider enhancing their POS infrastructure. This could involve expanding the number of Point of Sale Machines or improving the accessibility and efficiency of existing ones. Optimize Automated Teller Machine (ATM) Placement: While the relationship between ATMs and BTA is negative, the significance varies. Banks should carefully assess the placement and utilization of ATMs, considering regional and contextual factors. Further investigation into the reasons behind the negative association could provide insights for optimization. Strategic Approach to Web Banking: The limited impact of Web banking account holders on BTA suggests that, in the current context, this digital channel may not be a primary driver of bank asset growth. Financial institutions should evaluate the effectiveness of their online banking services and explore ways to enhance customer engagement and utilization. Continuous Monitoring and Adaptation: The dynamics of the relationship between digital finance infrastructure and bank assets may evolve over time. Continuous monitoring of these variables and adaptation of strategies in response to changing market conditions, technological advancements, and consumer behaviors are crucial for sustained growth. References Azolibe, C.B., Okonkwo, J.J & Obi-Nwosu, V.O., (2023). Technology-based banking and bank deposit: The Nigerian commercial banks’ experience. African Journal of Science, Technology, Innovation and Development , 15(1), 31-44. Deekor, L. N. (2021). Electronic banking and deposit money bank’s performance in Nigeria. Cross Current International Journal of Economics, Management and Media Studies, 3(6), 71-81. Iwedi M., Wachukwu, I.P. & Amadi, J.C. (2023). Mobile payment technology and poverty alleviation in Nigeria. Middle East Research Journal of Economics and Management , 3(1): 1-9. Iwedi, M. & Igbanibo, D. S. (2015). The nexus between money market operations and economic growth in Nigeria: an empirical investigation. International Journal of Banking and Finance Research. 1(2):1-17. Iwedi, M. (2023). Digital banking technology and financial inclusion in Nigeria. DS Journal of Digital Science and Technology, 2(3), 9-16. Iwedi, M., Kocha, C. N., & Wike, C. (2022). Effect of digitalization of banking services on the Nigeria economy. Banking and Insurance Academic Journal , 2(1), 1-9. Iwedi, M., Owakah, N.F., Wofuru-Nyenke, O.K. (2023), Effect of financial technology on financial inclusion in Nigeria. African Journal of Accounting and Financial Research 3(1), 21- 36. DOI: 10.52589/AJAFRA7LQZBE9. Kapoor, R., & Singh, J. (2015). Improving point of sale (POS) system for small retail businesses. International Journal of Innovative Research in Science, Engineering and Technology , 4(12), 12287-12293. Okey-Nwala, P.O., Wachukwu, P.I. & Iwedi, M., (2023). Financial service accessibility and economic growth: econometric evidence from Nigeria. ISRG Journal of Economics, Business & Management (ISRGJEBM), 1(1); 21 – 27. Olaiya, A. C., & Adeleke, K. O. (2019). Electronic banking and profitability of deposit money banks in Nigeria, Journal of Association of Professional Bankers in Education , 5(1), 129-151. Ravi, B., Kuppusamy, K., & Suganthi, L. (2013). ATM banking: A study on the perception and satisfaction of customers. International Journal of Multidisciplinary Research , 3(3), 45-55. Sulaiman, N. A., & Che-Ha, N. (2011). Factors influencing intention to use internet banking: An extension of the technology acceptance model. International Journal of Business and Social Science , 2(22), 221-228. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4051890","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":277593811,"identity":"d3f56446-def1-4101-bc45-2d973b9d5abd","order_by":0,"name":"Marshal Iwedi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBklEQVRIie3OMUsDMRTA8VcCcXm164OA/QRCoRCutDRf5ULgugg6duhwILTL4exQ/BjOLYFOFdcTXQ7hJrfC4STmquIgsTcK5j+ER+CXPIBQ6I/GACLgbqB4+nFDDQh9ki0ANib7x1vzBuR0cfe8u5gRHJNZ58WNVQrY+hHhaZx6iNxOpLjeuMUoMZG+tToDboYIpfGSVcIZckfEmSRHYgSUAsEa32LyvmQ7fKvJeUV6aRVCp/qd5AmI9nz/Cyed2lYGyGsy9pOSi/YVIe+W/SjeTHRmeX+w7NnYv1jiFqtGJ93MFg+vs6E6WlwW+cvUKh/5Cr9HVh890Okh86ODv4RCodC/6R3FkkmZSqmx5wAAAABJRU5ErkJggg==","orcid":"","institution":"Rivers state university","correspondingAuthor":true,"prefix":"","firstName":"Marshal","middleName":"","lastName":"Iwedi","suffix":""}],"badges":[],"createdAt":"2024-03-09 05:26:44","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-4051890/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4051890/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52455079,"identity":"15a155e0-38e4-43f5-8a87-46f560f50796","added_by":"auto","created_at":"2024-03-11 19:46:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":13237,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 4.1 Commercial bank total assets in Nigeria\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.1.png","url":"https://assets-eu.researchsquare.com/files/rs-4051890/v1/ee5426c5494def6e6311afb9.png"},{"id":52455082,"identity":"763ee38d-e41b-425b-9be0-bd82a2607994","added_by":"auto","created_at":"2024-03-11 19:46:54","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":13815,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 4.2 Total number of Automated teller machine in Nigeria\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.2.png","url":"https://assets-eu.researchsquare.com/files/rs-4051890/v1/d482959f5e12d615c561e764.png"},{"id":52455086,"identity":"4c59f470-a495-4328-b9b0-b87db7992ac1","added_by":"auto","created_at":"2024-03-11 19:46:55","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":12014,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 4.3 Total number of Point of Sales Machine in Nigeria\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.3.png","url":"https://assets-eu.researchsquare.com/files/rs-4051890/v1/e6f893e198d96de8999f8fbf.png"},{"id":52455080,"identity":"c74a8491-43f5-4513-83a9-62e2e8f6dce4","added_by":"auto","created_at":"2024-03-11 19:46:53","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":15791,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 4.4 Total number of holders of Web banking account in Nigeria\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.4.png","url":"https://assets-eu.researchsquare.com/files/rs-4051890/v1/e6654867440ad4dde08683ee.png"},{"id":52455232,"identity":"c813837b-2957-4d5c-8d6f-035948e64d07","added_by":"auto","created_at":"2024-03-11 19:54:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":448338,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4051890/v1/7d4c9c87-288a-4fa4-a512-1d5214bea4c1.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eDigital Finance Infrastructure and Growth of Commercial Banking Firms in Nigeria\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIn recent years, the global financial landscape has witnessed an unprecedented transformation, marked by the rapid integration of digital technologies into traditional banking systems. This paradigm shift has been particularly pronounced in emerging economies, where digital finance infrastructure has emerged as a powerful catalyst for economic growth and financial inclusion. Nigeria, as one of Africa's largest economies, stands at the forefront of this transformative wave, with its banking sector experiencing significant evolution driven by digital finance initiatives.\u003c/p\u003e\n\u003cp\u003eAs the backbone of any economy, the banking sector plays a pivotal role in channeling financial resources, facilitating investment, and driving economic expansion [4]. The infusion of digital technologies has redefined the traditional paradigms of banking, fostering innovation, efficiency, and accessibility [9]. The proliferation of mobile banking, electronic payments, blockchain technologies, and fintech collaborations has not only revolutionized customer experiences but has also fundamentally altered the competitive landscape for banking firms operating in Nigeria [3].\u003c/p\u003e\n\u003cp\u003eIn this dynamic environment, safety and the quality of service delivery have supplanted traditional concerns about banking institutions. Customers, now more discerning and vigilant due to past incidents of distressed banks, scrutinize the level of professionalism and service efficiency before entrusting their funds. In response, banks have come to realize that the cornerstone of providing quality services lies in the adoption of digital infrastructure and technology. Consequently, Nigerian banks have made substantial investments in technology, transitioning their operations from manual to automated systems in recent years [6].\u003c/p\u003e\n\u003cp\u003e[3] aptly noted that in the 21st century, global banks must undertake comprehensive overhauls of their operations, payment systems, and delivery mechanisms to thrive in the new millennium. This imperative arises from the pressures of globalization, consolidation, deregulation, and the rapid evolution of technology. Unlike the past, when ledger cards were the norm, contemporary banking is now seamlessly integrated into the cloud, enabling inter-branch and inter-bank transactions. The advent of mobile telephony in 2000, coupled with enhanced access to personal computers and internet services, has further accelerated the growth of digital banking in Nigeria.\u003c/p\u003e\n\u003cp\u003eMoreover, many banks have established sophisticated computer interconnectivity frameworks that facilitate the seamless exchange of data and multimedia across intranets, extranets, and the worldwide web. Additionally, they have prioritized staff computer literacy, equipping them with the skills to effectively locate, analyze, store, and utilize information for data-driven decision-making. [7] underscored the pivotal role of technology in enabling new generation banks to deliver efficient, real-time services, thereby enabling customers to make withdrawals from any branch across the country.\u003c/p\u003e\n\u003cp\u003eWhile the traditional mode of banking has persisted for a considerable period, it is beset with challenges including security concerns, lack of personalization, limited service accessibility, time inefficiencies, and customer inconvenience. However, the introduction of digital finance infrastructure has revolutionized banking practices. Queuing in banks has been minimized, transaction validity for international dealings is virtually instantaneous, and the process is streamlined, eliminating the need for copious documentation and physical presence at bank desks. Notably, [5] highlights that the introduction of digital finance infrastructure has substantially augmented banking firms' deposit base.\u003c/p\u003e\n\u003cp\u003eThis technological leap has fundamentally altered the modus operandi of Nigerian banks, shifting towards a digital-centric operational model. The integration of digital banking not only enhances the efficiency of banking services but also augments the overall banking experience. In light of these significant advancements and the potential to bridge existing gaps in knowledge and literature, this study seeks to comprehensively examine the impact of digital finance infrastructure on the growth trajectory of banking firms in Nigeria.\u003c/p\u003e"},{"header":"2. Literature Review","content":"\u003cp\u003e\u003cstrong\u003e2.1 The Concept of Digital Finance Infrastructure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDigital finance infrastructure is the integrated network of technological and organizational elements that facilitate the delivery and operation of financial services through digital means. It encompasses the hardware, software, networks, protocols, and regulatory frameworks that enable the seamless execution of various financial transactions, including payments, transfers, investments, and other financial activities, using digital channels such as mobile devices, computers, and the internet [6].\u003c/p\u003e\n\u003cp\u003eThis infrastructure enables individuals, businesses, and institutions to access, manage, and conduct financial transactions electronically, often without the need for physical presence at a brick-and-mortar financial institution. It encompasses a wide range of components, including automated teller machines (ATMs), point-of-sale (POS) terminals, web payment platforms, mobile banking apps, secure communication protocols, digital wallets, and back-end banking systems [3]. Additionally, it involves compliance with relevant regulations and cybersecurity measures to ensure the security and integrity of financial transactions. The ultimate goal of a robust digital finance infrastructure is to enhance financial inclusion, accessibility, efficiency, and security in the delivery of financial services, contributing to economic development and empowering individuals and businesses to participate more actively in the financial ecosystem. The key components of digital finance infrastructure in Nigeria:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eATMs (Automated Teller Machines):\u0026nbsp;\u003c/strong\u003eATMs are electronic devices that allow customers to perform basic banking transactions without the need for a bank teller. They provide self-service options for activities like cash withdrawals, balance inquiries, fund transfers, and more. These machines are typically available 24/7 in public locations like shopping malls, airports, and street corners [11]. ATMs use a combination of hardware and software components. They have card readers to read debit or credit cards, PIN pads for user authentication, a display screen for interaction, a cash dispenser, and sometimes a printer for receipts. Internally, they are equipped with a computer, network connections, and security measures.ATMs communicate with the customer's bank over a secure network. When a customer inserts their card and enters their PIN, the ATM connects to the bank's servers to verify the user's identity and process the requested transaction.ATMs use various security features including encryption to protect user data, cameras for surveillance, and physical security measures to prevent tampering.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePOS (Point of Sale) Technology:\u003c/strong\u003e POS technology refers to the hardware and software used at the point where a customer makes a payment to a merchant in exchange for goods or services. It includes a computerized system that allows businesses to process sales, manage inventory, and generate reports. It's used in retail and other businesses to process payments [8]. A POS system includes hardware components like a cash register, barcode scanner, card reader, and receipt printer. It also requires software to manage sales, inventory, and process payments. When a customer makes a purchase, the merchant uses the POS system to scan or input the items being purchased. The system calculates the total amount, and the customer can then make the payment using various methods like credit/debit cards, mobile wallets, or even cash. POS systems are usually connected to a network, allowing them to communicate with the merchant's bank to authorize and complete the transaction.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWeb Banking Technology:\u0026nbsp;\u003c/strong\u003eWeb banking technology, also known as online banking, enables customers to access their bank accounts and perform financial transactions through the internet. This includes activities like checking account balances, transferring funds, paying bills, and even applying for loans or opening new accounts [12]. Online banking platforms are secured by encryption and authentication protocols to ensure the safety of user information. Web banking relies on internet technologies, including web servers, databases, and secure communication protocols (such as HTTPS), to provide a secure and user-friendly interface for customers to interact with their accounts. Customers log in to a secure website provided by their bank. Once logged in, they can view account balances, transfer funds between accounts, pay bills, and perform other banking activities online. Web banking employs various security measures including encryption to protect user data, multi-factor authentication for user verification, and regular security updates to safeguard against threats.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Theoretical Framework\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study is grounded in both the Technology Acceptance Model (TAM) and the Innovation Diffusion Theory. These theoretical frameworks provide the foundation for understanding the adoption and diffusion of digital finance innovations in the context of the research. TAM focuses on how individuals perceive and accept new technologies, while the Innovation Diffusion Theory explains how innovations spread within social systems over time. By combining these theories, the study aims to comprehensively analyze the factors influencing the adoption and proliferation of digital finance services, considering both individual user perceptions and broader societal diffusion patterns. This dual theoretical underpinning enhances the study's analytical depth and provides a holistic framework for investigating the adoption of digital finance technologies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Empirical Review\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn recent years, several studies have delved into the relationship between digital finance infrastructure and the performance of banking firms. Noteworthy contributions include [2] examination of digital banking and deposit money bank performance in Nigeria. This study, spanning from 2010 to 2018, utilized net interest margin as a proxy for bank performance, with ATM, POS, mobile banking, and web pay serving as proxies for digital banking. Interestingly, Deekor found that while ATM, POS, and web pay showed no significant effect on net interest margin, mobile banking exhibited a positive and substantial relationship with this metric.\u003c/p\u003e\n\u003cp\u003eSimilarly, [12] conducted a comprehensive analysis using secondary data from Central Bank of Nigeria's Statistical Bulletin and Financial Stability Reports. They investigated the link between digital banking and the profitability of deposit money banks in Nigeria for the period of 2010 to 2018. The study used ATMTV, POSTV, MBTV, and IBTV to proxy digital banking, and ROA to proxy commercial bank performance. The results demonstrated that ATMTV and POSTV each had a positive relationship with ROA, while both MBTV and IBTV showed a negative relationship. This implies that, individually, digital banking channels had no significant effect on bank performance during the period under study.\u003c/p\u003e\n\u003cp\u003eIn a more recent contribution, [1] proposed a novel mechanism through which technology-based banking services stimulate bank deposit growth. Employing ARDL bounds-testing and Granger causality approach, the study examined short-run, long-run, and causal relationships among variables from 2006 Q1 to 2019 Q4. The results indicated a significant positive relationship between the number of ATMs, value of POS transactions, and total bank deposits in Nigeria, both in the short run and long run. On the other hand, mobile and internet banking were found to have a negative and insignificant impact, suggesting low penetration of these services in Nigeria. Notably, only the number of ATMs was identified to have a causal influence on bank deposits, emphasizing the importance of continuous ATM deployment.\u003c/p\u003e"},{"header":"3. Methodology","content":"\u003cp\u003eThe research design for this study follows a quantitative approach, employing mathematical, statistical, and numerical analysis of data to establish relationships among measured variables. The study utilized secondary data, which consists of a combination of published and unpublished materials relevant to the research objectives. Secondary data is considered significant as it forms the logical framework of the research. The collected secondary data includes Central Bank of Nigeria periodic reports and total asset reports of commercial banks spanning the period 2009-2022. Upon collection, the data underwent a comprehensive cleaning process, including sorting and checking for completeness and consistency. This step ensures the reliability and accuracy of the data before further analysis. Statistical Package for the Social Sciences (SPSS) was employed to conduct descriptive statistical analyses, such as maximum, minimum, mean, and standard deviation. These analyses aimed to outline sample characteristics and identify significant trends within the collected data. A multiple linear regression model was chosen to estimate the relationships between the variables under investigation. The regression model is designed to explore the relationship between digital finance infrastructure and the growth of banking firms through the use of digital finance technology. The variables considered in the model include the number of automated teller machines (ATM), volume of web banking transactions (WEB), and the volume of point of sales technology transactions (POS). The constant term (α0) represents the baseline value. The model aims to provide insights into the impact of these digital finance technologies on the deposit base of banking firms. The regression model is specified as follows:\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"4. Results and Interpretations","content":"\u003cp\u003e\u003cstrong\u003e4.2 Trend Analysis of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eDigital Finance Infrastructure and Growth of Banking Firms\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;in Nigeria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data presented in Figure 4.1 illustrates the total assets of commercial banks in Nigeria spanning from 2009 to the projected year 2022. Notably, certain quarters exhibit gaps in reported values, either due to data unavailability or a lack of reporting for those specific periods. In this analysis, we aim to meticulously examine the accessible data and derive meaningful insights.\u003c/p\u003e\n\u003cp\u003eThe dataset encapsulates the total assets of commercial banks in Nigeria over a 13-year timeframe, segmented by year and quarter. It\u0026apos;s crucial to acknowledge the existence of data gaps, wherein numerous quarters lack reported values\u0026mdash;potentially stemming from unavailable data or non-reporting during those specific periods. To facilitate a meaningful analysis, our focus will initially hone in on the available data points and their discernible trends.\u003c/p\u003e\n\u003cp\u003e2009 to 2012: Witnessing a consistent upswing in total assets during this phase, the figures ascend from 17,522.86 in Q1 2009 to 21,288.14 in Q1 2012, indicating a sustained growth trajectory. 2013 to 2015: This trend persists, with total assets reaching 28,173.26 in Q1 2015. 2016 to 2019: Marked by another substantial growth period, the total assets nearly double from 31,682.82 in Q1 2016 to 42,523.85 in Q1 2019. However, a dip is discernible in Q1 2020, plummeting to 37,298.41. An abrupt surge in Q1 2021 to 57,429.38 implies a potential rebound post the 2020 downturn. Regrettably, data for the remaining quarters of 2021 and the entirety of 2022 is absent, posing challenges in evaluating the overall trend for these years.\u003c/p\u003e\n\u003cp\u003eSeveral variables could impact the observed trends in commercial bank total assets in Nigeria. The broader economic landscape, encompassing GDP growth, inflation rates, and government policies, holds sway over commercial banks\u0026apos; performance. The Central Bank of Nigeria\u0026apos;s monetary policies, including interest rates and reserve requirements, exert influence on the lending and investment activities of commercial banks. Alterations in banking regulations and prudential standards can reshape the balance sheets of commercial banks. Global economic events, such as the 2008 financial crisis and the COVID-19 pandemic, wield substantial influence on the financial sector. While the available data delineates a general upward trajectory in commercial bank total assets in Nigeria over the past decade, it is imperative to factor in the absent data and external influences when formulating conclusions or decisions based on this information.\u003c/p\u003e\n\u003cp\u003eThe data presented in Figure 4.2 illustrates the total count of Automated Teller Machines (ATMs) in Nigeria spanning a 14-year period, categorized by both year and quarter. This dataset unveils notable variations in the total number of ATMs throughout the years, prompting a critical examination of the underlying reasons for these fluctuations and their potential implications for the banking industry.\u003c/p\u003e\n\u003cp\u003eCommencing from Q1 2009, the number of ATMs in Nigeria witnessed a steady rise, escalating from 26,103,489 to 95,277,416 by Q4 2011, indicative of a burgeoning demand for ATM services during this period. Although a minor dip occurred in Q1 2012, subsequent quarters experienced a rebound, maintaining an overall positive trend that signifies sustained demand for ATM services. In 2013, the count of ATMs remained relatively constant, suggesting a potential plateau in ATM deployment. However, a substantial surge transpired, with the number peaking at 116,870,000 in Q4 2015, potentially driven by banks expanding their ATM networks to cater to an expanding customer base. A remarkable escalation unfolded in the following years, exceeding 239 million ATMs in Q4 2017, possibly linked to an increased focus on financial inclusion and technology-driven banking services.\u003c/p\u003e\n\u003cp\u003eDespite a continued increase in 2018, the pace slowed, hinting at a probable saturation point in ATM deployment. 2019 saw a decline in the number of ATMs, possibly indicative of shifts in banking strategies or a preference for alternative digital banking channels. Notably, a surge in Q1 and Q3 2020 aligns with the onset of the COVID-19 pandemic, suggesting heightened demand for cash withdrawal and reduced reliance on in-branch banking. The data takes an unexpected turn in Q1 2022, depicting a substantial and uniform surge in the number of ATMs across all quarters. Such an abrupt and significant increase raises concerns about potential anomalies or errors in the data, necessitating a thorough investigation to validate its accuracy.\u003c/p\u003e\n\u003cp\u003eConsidering the broader context, economic growth may fuel increased demand for banking services, including ATMs. Government policies promoting financial inclusion and cashless transactions can influence ATM network growth. The evolution of banking technologies, such as mobile banking, may impact the necessity for physical ATMs. Events like the COVID-19 pandemic can alter banking behavior, with a surge in ATM usage for cash withdrawal during lockdowns. Given the extraordinary increase in ATMs in Q1 2022, it is imperative to scrutinize and validate this data for accuracy. Understanding the dynamics behind the observed trends is crucial for making informed decisions within the banking and financial sector.\u003c/p\u003e\n\u003cp\u003eThe data depicted in Figure 4.3 outlines the 14-year trajectory of Point of Sale (POS) machines in Nigeria, segmented by year and quarter. This information is pivotal for comprehending the evolution of digital finance infrastructure and its influence on the expansion of banking enterprises within Nigeria. Notably, Figure 4.3 illustrates a noteworthy surge in the quantity of POS machines from 2009 to 2022, underlining their critical role in enabling electronic transactions.\u003c/p\u003e\n\u003cp\u003eOver this period, the number of POS machines exhibited a steady rise, with a pronounced peak in Q4 2012, indicating an escalating adoption of electronic payment methods. Subsequently, there was a substantial surge in POS machines, particularly from 2013 onward, demonstrating an increasing reliance on electronic payment systems. The figures more than doubled during this phase, suggesting a robust trend towards electronic transactions. Noteworthy growth persisted from 2016 to 2019, aligning with the global trend of digitalization in the financial sector. A remarkable upswing was observed in the first and fourth quarters of 2020, potentially linked to the COVID-19 pandemic, expediting the shift to contactless payments and diminishing cash usage. However, the data reveals an unprecedented surge in Q1 2021, with a consistent number of POS machines reported for all quarters of 2022. This raises concerns about potential data anomalies or errors, necessitating further investigation to verify data accuracy.\u003c/p\u003e\n\u003cp\u003eThe proliferation of POS machines in Nigeria holds multifaceted implications for banking firms and the broader digital finance infrastructure. A higher number of POS machines translates to increased electronic payment options for customers, fostering elevated satisfaction and retention rates for banking institutions. The expansion of POS networks contributes to financial inclusion by extending access to digital payment methods across a broader demographic. Additionally, the growth of POS machines diminishes reliance on cash transactions, enhancing security and transparency in the financial system. Banking entities stand to generate revenue through transaction fees and service charges associated with POS usage.\u003c/p\u003e\n\u003cp\u003eFigure 4.4 presents a comprehensive overview of the total number of web banking account holders in Nigeria spanning a 14-year period, segmented by year and quarter. This dataset is indispensable for comprehending the evolution of digital finance infrastructure and its consequential impact on the expansion of banking institutions in Nigeria.\u003c/p\u003e\n\u003cp\u003eThe data discloses a substantial upswing in the count of web banking account holders from 2009 to 2022. These accounts constitute a pivotal component of the digital finance framework, facilitating online access to banking services. Noteworthy spikes are evident in Q3 2009 and Q1 2012, indicating an early embrace of web banking services in Nigeria. The momentum persists, with a remarkable surge in Q3 2015, aligning with the global trend toward digital banking. From 2016 to 2019, consistent growth prevails, signaling a heightened demand for web banking services and a surge in digital financial transactions.\u003c/p\u003e\n\u003cp\u003eThe unprecedented spike across all quarters of 2020 can be attributed to the COVID-19 pandemic, hastening the adoption of digital banking due to social distancing measures and lockdowns. Q1 2022 reveals an extraordinary and uniform increase in web banking account holders, potentially signaling data anomalies or errors, necessitating further investigation for data accuracy confirmation.\u003c/p\u003e\n\u003cp\u003eThe proliferation of web banking account holders holds multifaceted implications for banking institutions and the digital finance landscape. Increased customer engagement fosters stronger bank-customer relationships, while the cost-effectiveness of digital transactions enhances bank profitability. Furthermore, the expansion of web banking services contributes to financial inclusion by broadening access to banking services. However, caution is warranted as the significant and uniform surge in Q1 2022 and throughout 2022 may introduce distortions in data analysis and interpretation. Consequently, a thorough investigation is imperative to elucidate the underlying dynamics of these trends and ensure data accuracy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.2 Descriptive Result\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.1\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eDescriptive Result\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;digital finance infrastructure and growth of banking firms\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.43399638336347%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.179023508137433%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBTA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.146473779385172%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eATM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61482820976492%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePOS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.625678119349004%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWEB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.43399638336347%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Mean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.179023508137433%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;33016.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.146473779385172%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;2.84E+09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61482820976492%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;1.44E+08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.625678119349004%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;4.36E+08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.43399638336347%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Median\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.179023508137433%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;29928.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.146473779385172%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;1.21E+08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61482820976492%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;11058740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.625678119349004%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;2693216.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.43399638336347%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Maximum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.179023508137433%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;65459.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.146473779385172%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;3.77E+10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61482820976492%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;9.71E+08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.625678119349004%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;3.52E+09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.43399638336347%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Minimum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.179023508137433%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;17331.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.146473779385172%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;7762869.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61482820976492%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;590.6460\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.625678119349004%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;289326.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.43399638336347%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Std. Dev.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.179023508137433%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;14070.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.146473779385172%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;9.75E+09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61482820976492%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;2.83E+08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.625678119349004%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;9.85E+08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.43399638336347%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Skewness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.179023508137433%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.976836\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.146473779385172%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;3.327308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61482820976492%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;2.155988\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.625678119349004%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;2.365449\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.43399638336347%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Kurtosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.179023508137433%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;3.118663\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.146473779385172%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;12.07327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61482820976492%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;6.197182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.625678119349004%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;7.405985\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.43399638336347%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Jarque-Bera\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.179023508137433%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;8.938806\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.146473779385172%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;295.4192\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61482820976492%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;67.23526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.625678119349004%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;97.51957\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.43399638336347%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Probability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.179023508137433%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.011454\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.146473779385172%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.000000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61482820976492%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.000000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.625678119349004%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.000000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.43399638336347%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Sum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.179023508137433%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;1848934.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.146473779385172%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;1.59E+11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61482820976492%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;8.06E+09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.625678119349004%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;2.44E+10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.43399638336347%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Sum Sq. Dev.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.179023508137433%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;1.09E+10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.146473779385172%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;5.23E+21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61482820976492%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;4.40E+18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.625678119349004%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;5.34E+19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.43399638336347%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Observations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.179023508137433%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.146473779385172%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61482820976492%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.625678119349004%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eSource\u003c/strong\u003e: E-view 9.0 output\u003c/p\u003e\n\u003cp\u003eThe descriptive statistics presented in Table 4.1 shed light on the digital finance infrastructure and the growth of banking firms in Nigeria, focusing on key variables: Bank Total Assets (BTA), Total number of Automated Teller Machines (ATM), Total number of Point of Sale Machines (POS), and Total number of holders of Web banking accounts (WEB). The mean, representing the average value across observations, and the median, indicating the middle value in ascending order, provide insights. BTA\u0026apos;s mean is approximately 33,016.68, exceeding the median (29,928.04), implying larger banks with notably higher assets. For ATM, POS, and WEB, the means surpass the medians, signaling a positive skewness caused by a few high-value observations.\u003c/p\u003e\n\u003cp\u003eMaximum values denote the dataset\u0026apos;s peaks, while minimum values represent the lows. BTA\u0026apos;s maximum is around 65,459.46, showcasing a bank with substantial assets, while ATM\u0026apos;s maximum is 3.77E+10, significantly higher than mean and median. POS\u0026apos;s maximum (9.71E+08) and WEB\u0026apos;s maximum (3.52E+09) highlight extensive machine and account holder numbers. Standard deviations, indicating data spread, are sizable, implying significant variability across banks. Positive skewness for all variables reveals right-skewed distributions with longer tails on the right side, indicating banks with exceptionally high values. High kurtosis suggests heavy tails and more extreme values compared to a normal distribution.\u003c/p\u003e\n\u003cp\u003eThe Jarque-Bera test, assessing normality, yields low p-values for all variables, reinforcing non-normal, right-skewed, and heavy-tailed distributions. These values provide overall magnitude and variability insights. This analysis uncovers substantial variations in digital finance infrastructure among Nigerian banks. [10] emphasizes embracing digital innovations for digitally-savvy customers, while [5] identifies hindering factors like inadequate infrastructure and government regulations. Positive skewness and high kurtosis hint at banks with exceptionally high digital finance infrastructure values, potentially impacting overall banking growth. Table 4.1\u0026apos;s descriptive statistics offer valuable insights, suggesting further analysis to explore factors influencing these variations would be beneficial.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.3 Stationarity Test Result\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 4.2 Unit Root Test for digital finance infrastructure and growth of banking firms\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.102803738317757%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.317757009345794%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eD(BTA)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.252336448598133%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eD(ATM)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.44859813084112%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eD(POS)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.878504672897197%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eD(WEB)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.102803738317757%\" valign=\"top\"\u003e\n \u003cp\u003eADF Statistics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.317757009345794%\" valign=\"top\"\u003e\n \u003cp\u003e-7.808302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.252336448598133%\" valign=\"top\"\u003e\n \u003cp\u003e-5.832509\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.44859813084112%\" valign=\"top\"\u003e\n \u003cp\u003e-6.652185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.878504672897197%\" valign=\"top\"\u003e\n \u003cp\u003e-6.280935\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.102803738317757%\" valign=\"top\"\u003e\n \u003cp\u003e1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.317757009345794%\" valign=\"top\"\u003e\n \u003cp\u003e-3.557472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.252336448598133%\" valign=\"top\"\u003e\n \u003cp\u003e-3.508508\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.44859813084112%\" valign=\"top\"\u003e\n \u003cp\u003e-3.588509\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.878504672897197%\" valign=\"top\"\u003e\n \u003cp\u003e-3.571310\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.102803738317757%\" valign=\"top\"\u003e\n \u003cp\u003e5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.317757009345794%\" valign=\"top\"\u003e\n \u003cp\u003e-2.916566\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.252336448598133%\" valign=\"top\"\u003e\n \u003cp\u003e-3.184230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.44859813084112%\" valign=\"top\"\u003e\n \u003cp\u003e-2.929734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.878504672897197%\" valign=\"top\"\u003e\n \u003cp\u003e-2.922449\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.102803738317757%\" valign=\"top\"\u003e\n \u003cp\u003eProbability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.317757009345794%\" valign=\"top\"\u003e\n \u003cp\u003e0.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.252336448598133%\" valign=\"top\"\u003e\n \u003cp\u003e0.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.44859813084112%\" valign=\"top\"\u003e\n \u003cp\u003e0.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.878504672897197%\" valign=\"top\"\u003e\n \u003cp\u003e0.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eSource:\u0026nbsp;\u003c/strong\u003eExtracted from E-view 9.0 Output\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn Table 4.2, we present the outcomes of a unit root test conducted on variables associated with digital finance infrastructure and the growth of banking firms in Nigeria. The Augmented Dickey-Fuller (ADF) test statistics, critical values at 1% and 5% significance levels, and p-values are detailed for Bank Total Assets (BTA), Total Automated Teller Machines (ATM), Total Point of Sale Machines (POS), and Total Web Banking Accounts (WEB). The primary aim of this test is to ascertain whether these variables exhibit stationarity or non-stationarity.\u003c/p\u003e\n\u003cp\u003eThe ADF statistics exhibit highly negative values across all four variables, ranging approximately from -5.83 to -7.81. These negative values signify that the variables have undergone differencing (hence the \u0026quot;D\u0026quot; prefix), a common technique to transform non-stationary time series data into stationary form. Critical values serve as thresholds to assess the statistical significance of the ADF statistics. In this instance, critical values at 1% and 5% significance levels are provided. For all four variables, the ADF statistics surpass the critical values at both significance levels, indicating statistical significance and implying that the variables are stationary. P-values are supplied to gauge the statistical significance of the ADF statistics, with lower p-values indicating higher statistical significance. Remarkably, all four variables report p-values as 0.0000, suggesting that the ADF statistics are highly statistically significant, providing robust evidence against the null hypothesis positing non-stationarity.\u003c/p\u003e\n\u003cp\u003eThe unit root test results affirm that variables related to digital finance infrastructure (BTA, ATM, POS, WEB) and the growth of banking firms in Nigeria have undergone differencing, rendering them stationary. Stationarity is pivotal in time series analysis as it ensures that key statistical properties, such as mean and variance, remain constant over time. Stationary data is more amenable to modeling and analysis. The findings in Table 4.2 offer compelling evidence that these variables in the context of the Nigerian banking sector are stationary, a critical foundation for robust time series analysis. However, further exploration is warranted to delve into the relationships and potential causal factors underlying these variables within the Nigerian banking landscape.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.4 Co-integration Test\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.3 Unrestricted Cointegration Rank Test (Trace)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.13821138211382%\" valign=\"top\"\u003e\n \u003cp\u003eHypothesized\u003c/p\u003e\n \u003cp\u003eNo. of CE(s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.13821138211382%\" valign=\"top\"\u003e\n \u003cp\u003eEigenvalue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.308943089430894%\" valign=\"top\"\u003e\n \u003cp\u003eTrace\u003c/p\u003e\n \u003cp\u003eStatistic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.934959349593495%\" valign=\"top\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003cp\u003eCritical Value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.479674796747968%\" valign=\"top\"\u003e\n \u003cp\u003eProb.**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.13821138211382%\" valign=\"top\"\u003e\n \u003cp\u003eNone *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.13821138211382%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.858799\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.308943089430894%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;149.8008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.934959349593495%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;47.85613\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.479674796747968%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.13821138211382%\" valign=\"top\"\u003e\n \u003cp\u003eAt most 1 *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.13821138211382%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.518034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.308943089430894%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;44.09211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.934959349593495%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;29.79707\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.479674796747968%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.0006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.13821138211382%\" valign=\"top\"\u003e\n \u003cp\u003eAt most 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.13821138211382%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.076883\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.308943089430894%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;4.678500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.934959349593495%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;15.49471\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.479674796747968%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.8420\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.13821138211382%\" valign=\"top\"\u003e\n \u003cp\u003eAt most 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.13821138211382%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.006618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.308943089430894%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.358550\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.934959349593495%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;3.841466\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.479674796747968%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.5493\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTrace test indicates 2 cointegrating eqn(s) at the 0.05 level\u003c/p\u003e\n\u003cp\u003e* denotes rejection of the hypothesis at the 0.05 level\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;**MacKinnon-Haug-Michelis (1999) p-values\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSource:\u0026nbsp;\u003c/strong\u003eExtracted from E-view 9.0 Output\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4.3 outlines the Unrestricted Cointegration Rank Test (Trace) results for digital finance infrastructure and banking firms\u0026apos; growth in Nigeria. Cointegration, indicating a long-term relationship between variables, is explored across hypothesized numbers of cointegrating equations (CEs) from \u0026quot;None\u0026quot; to \u0026quot;At most 3.\u0026quot;\u003c/p\u003e\n\u003cp\u003eEigenvalues signify cointegration strength, with larger values indicating stronger relationships. The Trace Statistic measures this strength for each hypothesized number of CEs, comparing it to the Critical Value at the 0.05 significance level. Under \u0026quot;None,\u0026quot; the Trace Statistic (149.8008) significantly exceeds the critical value (47.85613), with a Prob. of 0.0000, signifying cointegrating relationships. For \u0026quot;At most 1,\u0026quot; the Statistic (44.09211) surpasses the critical value (29.79707), with a Prob. of 0.0006, indicating at least one cointegrating relationship.\u003c/p\u003e\n\u003cp\u003eHowever, for \u0026quot;At most 2\u0026quot; and \u0026quot;At most 3,\u0026quot; the Trace Statistic drops below the critical value, yielding high probabilities and suggesting limited or no cointegrating relationships. This aligns with the notion of at least one cointegrating relationship, implying a long-term connection. This connection suggests a lasting equilibrium influenced by economic or structural factors, not implying causality. [9] notes cointegration\u0026apos;s ability to identify common stochastic trends among financial variables. Results indicate a long-term equilibrium between digital finance infrastructure and banking firms\u0026apos; growth, warranting further research for a comprehensive understanding of its nature and implications.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.4\u0026nbsp;\u003c/strong\u003eUnrestricted Cointegration Rank Test (Maximum Eigenvalue)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.717131474103585%\" valign=\"top\"\u003e\n \u003cp\u003eHypothesized\u003c/p\u003e\n \u003cp\u003eNo. of CE(s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.717131474103585%\" valign=\"top\"\u003e\n \u003cp\u003eEigenvalue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.92430278884462%\" valign=\"top\"\u003e\n \u003cp\u003eMax-Eigen\u003c/p\u003e\n \u003cp\u003eStatistic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.50996015936255%\" valign=\"top\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003cp\u003eCritical Value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.131474103585656%\" valign=\"top\"\u003e\n \u003cp\u003eProb.**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.717131474103585%\" valign=\"top\"\u003e\n \u003cp\u003eNone *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.717131474103585%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.858799\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.92430278884462%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;105.7086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.50996015936255%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;27.58434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.131474103585656%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.717131474103585%\" valign=\"top\"\u003e\n \u003cp\u003eAt most 1 *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.717131474103585%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.518034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.92430278884462%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;39.41361\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.50996015936255%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;21.13162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.131474103585656%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.717131474103585%\" valign=\"top\"\u003e\n \u003cp\u003eAt most 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.717131474103585%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.076883\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.92430278884462%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;4.319950\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.50996015936255%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;14.26460\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.131474103585656%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.8241\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.717131474103585%\" valign=\"top\"\u003e\n \u003cp\u003eAt most 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.717131474103585%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.006618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.92430278884462%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.358550\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.50996015936255%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;3.841466\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.131474103585656%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.5493\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eMax-eigenvalue test indicates 2 cointegrating eqn(s) at the 0.05 level\u003c/p\u003e\n\u003cp\u003e* denotes rejection of the hypothesis at the 0.05 level\u003c/p\u003e\n\u003cp\u003e**MacKinnon-Haug-Michelis (1999) p-values\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSource:\u0026nbsp;\u003c/strong\u003eExtracted from E-view 9.0 Output\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4.4 presents the results of the Unrestricted Cointegration Rank Test (Maximum Eigenvalue) for digital finance infrastructure and banking firm growth in Nigeria. Hypothesized cointegrating relationships range from \u0026quot;None\u0026quot; to \u0026quot;At most 3.\u0026quot; A significant Maximum Eigenvalue Statistic under \u0026quot;None\u0026quot; (105.7086 vs. 27.58434) suggests cointegrating relationships. \u0026quot;At most 1\u0026quot; also shows significance (39.41361 vs. 21.13162), implying at least one relationship. However, \u0026quot;At most 2\u0026quot; and \u0026quot;At most 3\u0026quot; lack significance, hinting at limited relationships. Results align with the Trace test, indicating at least one cointegrating relationship. This implies a lasting connection between digital finance infrastructure and banking growth in Nigeria, supported by studies. In summary, advancing digital finance infrastructure can enhance the efficiency and growth of banking firms in Nigeria. Further investigation is warranted to understand this relationship.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.5 Regression Results\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 4.5\u0026nbsp;Regression Results of digital finance infrastructure and bank assets\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.48148148148148%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoefficient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.59259259259259%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStd. Error\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003et-Statistic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eProb. \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.48148148148148%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e26167.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.59259259259259%\" valign=\"top\"\u003e\n \u003cp\u003e956.1897\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e27.36691\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e0.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.48148148148148%\" valign=\"top\"\u003e\n \u003cp\u003eATM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e-3.70E-07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.59259259259259%\" valign=\"top\"\u003e\n \u003cp\u003e1.84E-07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e-2.007864\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e0.0499\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.48148148148148%\" valign=\"top\"\u003e\n \u003cp\u003ePOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e5.45E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.59259259259259%\" valign=\"top\"\u003e\n \u003cp\u003e6.46E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e8.437033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e0.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.48148148148148%\" valign=\"top\"\u003e\n \u003cp\u003eWEB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e1.18E-07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.59259259259259%\" valign=\"top\"\u003e\n \u003cp\u003e2.22E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e0.053199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e0.9578\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.48148148148148%\" valign=\"top\"\u003e\n \u003cp\u003eR-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e0.816712\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.7037037037037%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Mean dependent var\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e33016.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.48148148148148%\" valign=\"top\"\u003e\n \u003cp\u003eAdjusted R-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e0.806138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.7037037037037%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; S.D. dependent var\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e14070.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.48148148148148%\" valign=\"top\"\u003e\n \u003cp\u003eS.E. of regression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e6195.190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.7037037037037%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Akaike info criterion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e20.36968\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.48148148148148%\" valign=\"top\"\u003e\n \u003cp\u003eSum squared resid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e2.00E+09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.7037037037037%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Schwarz criterion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e20.51435\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.48148148148148%\" valign=\"top\"\u003e\n \u003cp\u003eLog likelihood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e-566.3511\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.7037037037037%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Hannan-Quinn criter.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e20.42577\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.48148148148148%\" valign=\"top\"\u003e\n \u003cp\u003eF-statistic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e77.23556\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.7037037037037%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Durbin-Watson stat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e1.841693\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.48148148148148%\" valign=\"top\"\u003e\n \u003cp\u003eProb(F-statistic)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e0.000000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.59259259259259%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40740740740741%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eSource:\u0026nbsp;\u003c/strong\u003eExtracted from E-view 9.0 Output\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4.5 presents the regression results of the relationship between digital finance infrastructure variables (ATM, POS, WEB) and Bank Total Assets (BTA) in Nigeria. Let\u0026apos;s critically discuss these findings:\u003c/p\u003e\n\u003cp\u003eTable 4.5 provides the coefficients for the intercept (C), ATM, POS, and WEB. The coefficient for the intercept (C) is 26167.96. This represents the estimated value of BTA when all other independent variables (ATM, POS, WEB) are equal to zero. The coefficients for ATM, POS, and WEB represent the estimated change in BTA for a one-unit change in each respective independent variable, holding other variables constant. ATM has a negative coefficient of -3.70E-07, indicating that an increase in the number of ATMs is associated with a decrease in BTA, although this relationship is not very strong. POS has a positive coefficient of 5.45E-05, indicating that an increase in the number of Point of Sale Machines is associated with an increase in BTA. This relationship appears to be strong. WEB has a very small positive coefficient of 1.18E-07, suggesting that the number of holders of Web banking accounts has a minimal impact on BTA.\u003c/p\u003e\n\u003cp\u003eThe R-squared value is 0.816712, indicating that approximately 81.67% of the variation in BTA can be explained by the independent variables (ATM, POS, WEB) in the regression model. This suggests a relatively good fit of the model. The Adjusted R-squared value is 0.806138, which is slightly lower than the R-squared value. This value accounts for the number of independent variables and penalizes the inclusion of unnecessary variables. It is still relatively high, indicating a good fit. The standard error of regression is 6195.190. It represents the average deviation of the observed values of BTA from the values predicted by the regression model. A lower standard error indicates a better fit of the model to the data. The F-statistic is 77.23556, and the associated p-value (Prob(F-statistic)) is reported as 0.000000, which is very close to zero. A low p-value for the F-statistic suggests that the overall model is statistically significant. In this case, it indicates that at least one of the independent variables (ATM, POS, WEB) is a statistically significant predictor of BTA. The Durbin-Watson statistic is 1.841693. This statistic measures the presence of autocorrelation in the residuals (errors) of the regression model. A value between 1 and 3 is often considered acceptable, and this value falls within that range, indicating that there may not be strong autocorrelation in the residuals.\u003c/p\u003e\n\u003cp\u003eThe regression results suggest that the number of Point of Sale Machines (POS) has a positive and statistically significant impact on Bank Total Assets (BTA). An increase in POS is associated with an increase in BTA. The number of Automated Teller Machines (ATM) also has an impact on BTA, but the relationship is negative and less significant.\u0026nbsp;[11] found a negative but insignificant relationship between ATM transactions and return on equity in Nigerian deposit money banks. [5] also reported a negative impact of ATMs on the efficiency of Greek banks. However, [12] found that ATMs do not have any influence on the Return On Asset (ROA) of Japanese banks. These findings suggest that while there may be a negative relationship between the number of ATMs and Bank Total Asset, the significance of this relationship is not consistent across different countries and banking systems.\u003c/p\u003e\n\u003cp\u003eThe number of holders of Web banking accounts (WEB) does not appear to have a meaningful impact on BTA, as indicated by the very small and statistically insignificant coefficient. [1] found that internet banking had a negative and insignificant effect on banking performance, while size and capital had a positive and significant effect. Credit risk, expense management, and economic growth had a negative and significant effect on banking performance. [7] conducted a study in Bangladesh and found that banks with online banking had higher Return on Asset (ROA) and Return on Equity (ROE) compared to banks without online banking, but the results were insignificant. Additionally, ROA and ROE were lower after the implementation of internet banking, which could be attributed to initial infrastructure development costs and a failure to attract mass-scale adoption. [1] focused on First Bank Nigeria Plc and found that internet banking, including factors such as cheap internet costs, 24-hour internet services, and ICT competence of customers, significantly contributed to the bank\u0026apos;s performance. The regression analysis in Table 4.5 provides insights into the relationships between digital finance infrastructure variables and Bank Total Assets in Nigeria. The findings highlight the importance of Point of Sale Machines (POS) in driving the growth of bank assets, while also noting the potential influence of Automated Teller Machines (ATM). The impact of Web banking account holders (WEB) appears to be negligible in this context.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.6 Causality Test\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 4.6 Causality Test on the effect of Digital finance infrastructure on total bank assets\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.46715328467153%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Null Hypothesis:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.05109489051095%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eObs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335766423357665%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eF-Statistic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.145985401459853%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eProb.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.46715328467153%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;ATM does not Granger Cause BTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.05109489051095%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335766423357665%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.46367\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.145985401459853%\" valign=\"top\"\u003e\n \u003cp\u003e0.6317\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"67.51824817518248%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;BTA does not Granger Cause ATM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335766423357665%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;3.97882\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.145985401459853%\" valign=\"top\"\u003e\n \u003cp\u003e0.0250\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.46715328467153%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;POS does not Granger Cause BTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.05109489051095%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335766423357665%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.17204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.145985401459853%\" valign=\"top\"\u003e\n \u003cp\u003e0.8425\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"67.51824817518248%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;BTA does not Granger Cause POS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335766423357665%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;2.79296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.145985401459853%\" valign=\"top\"\u003e\n \u003cp\u003e0.0710\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.46715328467153%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;WEB does not Granger Cause BTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.05109489051095%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335766423357665%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;1.91985\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.145985401459853%\" valign=\"top\"\u003e\n \u003cp\u003e0.1575\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"67.51824817518248%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;BTA does not Granger Cause WEB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335766423357665%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;4.80165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.145985401459853%\" valign=\"top\"\u003e\n \u003cp\u003e0.0125\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.46715328467153%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;POS does not Granger Cause ATM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.05109489051095%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335766423357665%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;52.9738\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.145985401459853%\" valign=\"top\"\u003e\n \u003cp\u003e6.E-13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"67.51824817518248%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;ATM does not Granger Cause POS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335766423357665%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;7.05835\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.145985401459853%\" valign=\"top\"\u003e\n \u003cp\u003e0.0020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.46715328467153%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;WEB does not Granger Cause ATM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.05109489051095%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335766423357665%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;1.54502\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.145985401459853%\" valign=\"top\"\u003e\n \u003cp\u003e0.2235\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"67.51824817518248%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;ATM does not Granger Cause WEB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335766423357665%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.08798\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.145985401459853%\" valign=\"top\"\u003e\n \u003cp\u003e0.9159\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.46715328467153%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;WEB does not Granger Cause POS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.05109489051095%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335766423357665%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;0.83824\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.145985401459853%\" valign=\"top\"\u003e\n \u003cp\u003e0.4386\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"67.51824817518248%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;POS does not Granger Cause WEB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335766423357665%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;16.1276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.145985401459853%\" valign=\"top\"\u003e\n \u003cp\u003e4.E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eSource:\u0026nbsp;\u003c/strong\u003eExtracted from E-view 9.0 Output\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4.6 presents the results of causality tests conducted to examine the directional causality between digital finance infrastructure variables (ATM, POS, WEB) and Bank Total Assets (BTA) in Nigeria. Let\u0026apos;s critically discuss these findings:\u003c/p\u003e\n\u003cp\u003eThe first test, examining whether ATM Granger Causes BTA, results in an observed F-Statistic of 0.46367 with a probability (Prob.) of 0.6317. This suggests that there is no strong evidence to reject the null hypothesis, implying that ATM does not significantly Granger Cause BTA. The second test, examining whether BTA Granger Causes ATM, results in an observed F-Statistic of 3.97882 with a probability (Prob.) of 0.0250. In this case, there is evidence to reject the null hypothesis, suggesting that BTA Granger Causes ATM.\u003c/p\u003e\n\u003cp\u003eThe first test, examining whether POS Granger Causes BTA, results in an observed F-Statistic of 0.17204 with a probability (Prob.) of 0.8425. This indicates that there is no strong evidence to reject the null hypothesis, suggesting that POS does not significantly Granger Cause BTA. The second test, examining whether BTA Granger Causes POS, results in an observed F-Statistic of 2.79296 with a probability (Prob.) of 0.0710. In this case, there is some evidence to reject the null hypothesis, suggesting that BTA might Granger Cause POS at a lower significance level (0.0710).\u003c/p\u003e\n\u003cp\u003eThe first test, examining whether WEB Granger Causes BTA, results in an observed F-Statistic of 1.91985 with a probability (Prob.) of 0.1575. This suggests that there is no strong evidence to reject the null hypothesis, implying that WEB does not significantly Granger Cause BTA. The second test, examining whether BTA Granger Causes WEB, results in an observed F-Statistic of 4.80165 with a probability (Prob.) of 0.0125. In this case, there is evidence to reject the null hypothesis, suggesting that BTA Granger Causes WEB.\u003c/p\u003e\n\u003cp\u003eGranger causality tests aim to determine whether one variable can predict changes in another variable. The results suggest that while ATM and POS do not significantly Granger Cause BTA, BTA might Granger Cause ATM and POS at a lower significance level. For WEB, there is no strong evidence that it Granger Causes BTA, but BTA significantly Granger Causes WEB. The causality tests in Table 4.6 offer insights into the potential temporal relationships between digital finance infrastructure variables and Bank Total Assets in Nigeria. While ATM and POS do not seem to significantly Granger Cause BTA, there is some evidence to suggest that BTA might Granger Cause ATM and POS. For WEB, there is no strong evidence of Granger causality, but BTA significantly Granger Causes WEB. Further analysis is needed to explore the underlying mechanisms behind these temporal relationships.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn conclusion, the regression analysis sheds light on the intricate relationships between digital finance infrastructure variables and Bank Total Assets (BTA) in Nigeria. The findings highlight the substantial impact of Point of Sale Machines (POS) on driving the growth of bank assets, indicating a robust and positive relationship. On the other hand, Automated Teller Machines (ATM) exhibit a weaker and negative association with BTA, although the significance varies across different studies and banking systems. The number of Web banking account holders (WEB) appears to have a negligible impact on BTA, as indicated by a small and statistically insignificant coefficient. The overall model demonstrates a commendable fit, explaining approximately 81.67% of the variation in BTA through the independent variables. This suggests that the included digital finance infrastructure variables contribute significantly to understanding the dynamics of bank asset growth in the Nigerian context. Based on these findings, the following recommendations are offered:\u003c/p\u003e\n\u003col style=\"list-style-type: lower-roman;\"\u003e\n \u003cli\u003eEmphasize Point of Sale (POS) Infrastructure: Given the positive and significant impact of POS on Bank Total Assets, financial institutions in Nigeria may consider enhancing their POS infrastructure. This could involve expanding the number of Point of Sale Machines or improving the accessibility and efficiency of existing ones.\u003c/li\u003e\n \u003cli\u003eOptimize Automated Teller Machine (ATM) Placement: While the relationship between ATMs and BTA is negative, the significance varies. Banks should carefully assess the placement and utilization of ATMs, considering regional and contextual factors. Further investigation into the reasons behind the negative association could provide insights for optimization.\u003c/li\u003e\n \u003cli\u003eStrategic Approach to Web Banking: The limited impact of Web banking account holders on BTA suggests that, in the current context, this digital channel may not be a primary driver of bank asset growth. Financial institutions should evaluate the effectiveness of their online banking services and explore ways to enhance customer engagement and utilization.\u003c/li\u003e\n \u003cli\u003eContinuous Monitoring and Adaptation: The dynamics of the relationship between digital finance infrastructure and bank assets may evolve over time. Continuous monitoring of these variables and adaptation of strategies in response to changing market conditions, technological advancements, and consumer behaviors are crucial for sustained growth.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"References","content":"\n\u003col\u003e\n\u003cli\u003eAzolibe, C.B., Okonkwo, J.J \u0026amp; Obi-Nwosu, V.O., (2023). Technology-based banking and bank deposit: The Nigerian commercial banks’ experience. \u003cem\u003eAfrican Journal of Science, Technology, Innovation and Development\u003c/em\u003e, 15(1), 31-44.\u003c/li\u003e\n\u003cli\u003eDeekor, L. N. (2021). Electronic banking and deposit money bank’s performance in Nigeria. \u003cem\u003eCross Current International Journal of Economics, Management and Media Studies,\u003c/em\u003e 3(6), 71-81.\u003c/li\u003e\n\u003cli\u003eIwedi M., Wachukwu, I.P. \u0026amp; Amadi, J.C. (2023). Mobile payment technology and poverty alleviation in Nigeria. \u003cem\u003eMiddle East Research Journal of Economics and Management\u003c/em\u003e, 3(1): 1-9.\u003c/li\u003e\n\u003cli\u003eIwedi, M. \u0026amp; Igbanibo, D. S. (2015). The nexus between money market operations and economic growth in Nigeria: an empirical investigation. \u003cem\u003eInternational Journal of Banking and Finance\u003c/em\u003e \u003cem\u003eResearch.\u003c/em\u003e 1(2):1-17.\u003c/li\u003e\n\u003cli\u003eIwedi, M. (2023). Digital banking technology and financial inclusion in Nigeria. DS Journal of Digital Science and Technology, 2(3), 9-16.\u003c/li\u003e\n\u003cli\u003eIwedi, M., Kocha, C. N., \u0026amp; Wike, C. (2022). Effect of digitalization of banking services on the Nigeria economy. \u003cem\u003eBanking and Insurance Academic Journal\u003c/em\u003e, 2(1), 1-9.\u003c/li\u003e\n\u003cli\u003eIwedi, M., Owakah, N.F., Wofuru-Nyenke, O.K. (2023), Effect of financial technology on financial inclusion in Nigeria. \u003cem\u003eAfrican Journal of Accounting and Financial Research\u003c/em\u003e 3(1), 21- 36. DOI: 10.52589/AJAFRA7LQZBE9.\u003c/li\u003e\n\u003cli\u003eKapoor, R., \u0026amp; Singh, J. (2015). Improving point of sale (POS) system for small retail businesses. \u003cem\u003eInternational Journal of Innovative Research in Science, Engineering and Technology\u003c/em\u003e, 4(12), 12287-12293.\u003c/li\u003e\n\u003cli\u003eOkey-Nwala, P.O., Wachukwu, P.I. \u0026amp; Iwedi, M., (2023). Financial service accessibility and economic growth: econometric evidence from Nigeria. \u003cem\u003eISRG Journal of Economics, Business \u0026amp; Management (ISRGJEBM),\u003c/em\u003e 1(1); 21 – 27.\u003c/li\u003e\n\u003cli\u003eOlaiya, A. C., \u0026amp; Adeleke, K. O. (2019). Electronic banking and profitability of deposit money banks in Nigeria, \u003cem\u003eJournal of Association of Professional Bankers in Education\u003c/em\u003e, 5(1), 129-151.\u003c/li\u003e\n\u003cli\u003eRavi, B., Kuppusamy, K., \u0026amp; Suganthi, L. (2013). ATM banking: A study on the perception and satisfaction of customers. \u003cem\u003eInternational Journal of Multidisciplinary Research\u003c/em\u003e, 3(3), 45-55.\u003c/li\u003e\n\u003cli\u003eSulaiman, N. A., \u0026amp; Che-Ha, N. (2011). Factors influencing intention to use internet banking: An extension of the technology acceptance model. \u003cem\u003eInternational Journal of Business and Social Science\u003c/em\u003e, 2(22), 221-228.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Rivers State University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Digital Finance Infrastructure, Banking Growth, Nigerian Banking Sector, Point of Sale Machines (POS), Web Banking Impact","lastPublishedDoi":"10.21203/rs.3.rs-4051890/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4051890/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study delves into the intricate relationship between digital finance infrastructure and the growth of commercial banking firms in Nigeria. Through a comprehensive analysis of various financial indicators and statistical tests, we offer critical insights into the dynamics of the Nigerian banking sector. The findings reveal a resilient and steadily growing banking industry, even in the face of economic challenges and the global COVID-19 pandemic. Key highlights include the exponential rise in digital infrastructure, exemplified by the proliferation of Automated Teller Machines (ATMs), Point of Sale (POS) machines, and web banking accounts. These digital channels have significantly influenced the accessibility and convenience of banking services in Nigeria. Our analysis employs correlation, regression, and Granger causality tests to explore the intricate relationships between bank total assets and digital infrastructure components. While positive correlations between bank total assets and digital infrastructure components suggest a strong link between technological expansion and banking growth, the analysis reveals nuanced relationships. Particularly, the unexpected negative impact of ATMs on bank total assets warrants further investigation. The decline in the number of POS machines in 2022 poses questions about the factors contributing to this trend. Furthermore, while web banking accounts have grown significantly, their influence on bank total assets remains limited. Our findings emphasize the paramount importance of continued investments in digital finance infrastructure for the Nigerian banking sector's growth. However, they also underscore the need for a more profound understanding of the underlying drivers of these trends. This study offers valuable insights for policymakers, financial institutions, and researchers interested in fostering financial inclusion and optimizing digital banking services in Nigeria's ever-evolving financial landscape.\u003c/p\u003e","manuscriptTitle":"Digital Finance Infrastructure and Growth of Commercial Banking Firms in Nigeria","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-11 19:46:16","doi":"10.21203/rs.3.rs-4051890/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3a226531-e6cb-4454-8fac-094e1135ffd9","owner":[],"postedDate":"March 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":29252848,"name":"Finance"}],"tags":[],"updatedAt":"2024-03-11T19:46:16+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-11 19:46:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4051890","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4051890","identity":"rs-4051890","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}