Pa ge 1 Pa ge 14 3 American Journal of Financial Technology and Innovation (AJFTI) Cloud-Based Accounting and Financial Performance of Listed Deposit Money Banks in Nigeria Ajibola, Hussein Olamilekan1*, Fasina, Oludare Olakunle1, Akinbode, Peter Sunday2 Volume 3 Issue 1, Year 2025 ISSN: 2996-0975 (Online) DOI: https://doi.org/10.54536/ajfti.v3i1.5653 https://journals.e-palli.com/home/index.php/ajfti Article Information ABSTRACT Received: July 05, 2025 Accepted: August 08, 2025 Published: September 10, 2025 With the financial environment changing so quickly these days, the Nigerian banking industry is under increasing pressure to modernize its operations, improve service quality, and maximize financial performance. One innovation that is becoming more popular is cloud accounting, which is a digital accounting paradigm that provides cost-effectiveness, scalability, and real-time data access. This study, therefore, examined cloud-based accounting and the financial performance of listed deposit money banks in Nigeria. The study employed ex-post facto research design. Ten of the 14 deposit money banks that were listed in Nigeria as of the end of 2024 were used as the sample size in this study. During the data extraction process, the study used secondary sources, specifically from the annual reports and accounts of the selected banks from 2015–2024. The data gathered was analyzed with the use of descriptive statistics, correlation and regression analysis. Software cost (β=7.966379, p-value = 0.0002) and training cost (β=12.50473, p-value = 0.0000) appeared to have a positive and significant impact on the return on assets of Nigerian listed deposit money banks, according to the regression results. As a result, the study came to the conclusion that software and training expenses may be used by current and prospective investors to predict the return on assets of the chosen deposit money banks in Nigeria. To facilitate the broad use of cloud-based accounting in Nigerian deposit money banks, the research suggested that the government, trade groups, and financial institutions emphasize training and skill development in technology infrastructure. Keywords Cloud-Based Accounting, Financial Performance, Return on Assets, Software Cost and Training Cost INTRODUCTION The performance of the financial services sector has a major influence on the whole economy, making it a pillar of economic growth. Deposit money banks are essential to the mobilization of savings, the granting of credit, and the facilitation of investment and commerce in Nigeria. However, because of rising competition, inefficiencies in conventional systems, and high operating expenses, these banks’ financial performance has been a recurring worry. A bank’s capacity to turn a profit, control expenses, and maintain its competitiveness in a changing market is largely reflected in its financial performance (Olokoyo et al., 2019). Due to the increasing need for operational efficiency and the quick development of technology, the global banking industry has undergone a substantial digital transformation in recent years. Cloud-based accounting has become one of these advances’ most important tools for increasing data accessibility, automating financial procedures, and boosting decision-making accuracy (Adebayo & Okonkwo, 2023). Using web-based software that is housed on distant servers to carry out accounting tasks including data entry, reporting, and analysis is known as cloud accounting. Banks and other companies may work together across branches or departments and access financial data in real-time with this paradigm (Ibrahim & Oladele, 2022). Adoption of cloud accounting is not free, but research shows that it improves asset usage overall. According to the research of Ofurum and Obi (2024), training expenses had a positive but negligible correlation with return on assets, but software acquisition costs had a negative but negligible correlation. By improving system usage and stability, this shows that initial investments in cloud-based accounting do not always degrade financial performance over time, increasing return on assets. In the quickly changing financial environment of today, the Nigerian banking industry is under increasing pressure to improve service delivery, modernize processes, and maximize financial performance. Cloud accounting is one innovation that is becoming more and more popular. It is a digital accounting paradigm that provides cost-effectiveness, scalability, and real-time data access. According to Adebayo and Okonkwo (2023), cloud- based accounting systems are widely acknowledged as strategic instruments that enhance organizational agility, decision-making, and the accuracy of financial reporting. But because to the Central Bank of Nigeria’s drive for digital innovation and safe data management, cloud-based technology adoption by Deposit Money Banks (DMBs) in Nigeria is progressively picking up steam (Ezeani & Udeh, 2024). Notwithstanding these advancements, a substantial knowledge vacuum still exists about the precise impact of cloud accounting adoption on financial performance in the Nigerian banking industry. There is still uncertainty over the financial rationale behind 1 Department of Accountancy, Federal Polytechnic Ilaro, Ogun State, Nigeria 2 Crown Heritage College of Health Technology and Management, Ilaro, Ogun State, Nigeria * Corresponding author’s e-mail: jblhussein@gmail.com Pa ge 14 4 https://journals.e-palli.com/home/index.php/ajfti Am. J. Financ. Technol. Innov. 3(1) 143-154, 2025 the migration of numerous Nigerian banks from conventional on-premises accounting systems to cloud- based platforms. According to Nwachukwu and Hassan (2025), these restrictions may make it more difficult to use cloud technologies effectively and raise questions about their capacity to improve important performance metrics like return on assets. Numerous deposit money institutions in Nigeria are still facing difficulties, including expensive software purchase and training expenses. According to Onifade et al. (2023), high software costs had a negative effect on Nigerian banks’ financial performance, indicating that such investments might not yield immediate returns without careful cost-benefit analysis. On the other hand, Ofurum and Obi (2024) showed that training investments can have a positive, albeit occasionally negligible, impact on financial performance, emphasizing the need for strategic training programs that are in line with organizational goals. The adoption of cloud-based accounting tends to improve return on assets (ROA), according to a number of studies, including those by Ezejofor et al. (2024), Ofurum & Obi (2024), Akadi & Olaoye (2024), Ebere et al. (2024), Ighosewe et al. (2024), Odunayo et al. (2023), Okika & Udeh (2023), Ajape et al. (2023), Onifade et al. (2023), Peters & Fred Horsfall (2023), Oyewobi & Adeyemi (2023), Daniel (2024), Ejabu & Edet (2024), Agaji (2023), and Odukwu et al. (2023). There are currently very few panel data studies that isolate these distinct cost influences on return on assets, which is the gap. This study fills that vacuum by assessing the impact of cloud-based accounting on financial performance of Nigerian listed deposit money institutions. In doing so, it aims to achieve the following specific objectives: i. To examine the effect of software cost on return on assets of listed Nigerian deposit money banks. ii. To evaluate how training costs affect return on assets of listed Nigerian deposit money banks. LITERATURE REVIEW Conceptual Review Financial Performance How successfully a company uses its assets to manage its operations and turn a profit is referred to as its financial performance. It analyzes a company’s overall financial health at a given time and may be used to evaluate how well a business is doing within its industry or across all sectors (Ajirole, 2019). One important source of data for assessing a company’s success is its financial statements, which are a result of accounting. They record sales, costs, and profits for a specific time period, as well as information on changes in owners’ wealth and the sources and uses of funds throughout that time (Ndukwe, 2018). Financial performance may be calculated or examined using a number of metrics, but each one concentrates on a different aspect of the performance (Folajimi et al., 2020). It shows the general state of a company’s finances over a given time frame. The technique of analyzing financial statements to determine an organization’s operational and financial characteristics is known as financial performance analysis; in this study, return on assets is used as a proxy for financial performance. Aduda et al. (2017) asserted that when assessing financial performance, ratio analysis is a helpful technique. It may be used to assess an organization’s financial efficiency, liquidity, profitability, and solvency ratios as well as its capacity to pay back loans within a given time period. For instance, Abdulazeez et al. (2018) used return on equity and return on asset to measure the performance of Nigerian listed conglomerate companies and their inventory management. Oladipupo and Okafor (2017), on the other hand, used return on assets and the Tobin Q ratio to gauge financial success. Return on assets, however, was used in this study as a stand-in for financial performance because it is one of the metrics that is most affected by poorly managed cloud-based accounting. Return on Assets (ROA) Return on assets is a crucial indicator of a manufacturing company’s profitability. It is defined as the ratio of revenue to total assets. It evaluates how well managers of manufacturing firms can use their resources to generate a profit. The efficiency with which the business uses its resources to generate income is also demonstrated. It further demonstrates how well business management makes use of all available resources to produce net income (Khrawish, 2017). According to Sehrish et al. (2019), ROA establishes the amount of profit generated per asset. It shows the effectiveness with which a business uses its assets or financial resources to generate profits. Simply said, ROA indicates management effectiveness and shows how well a manufacturing company’s management uses its resources to generate profits. A manufacturing company’s profitability or strong performance may be clearly determined by a high return on assets (ROA) ratio (Bentum, 2020). Cloud-Based Accounting Accounting software is often bought as a package and set up locally on a user’s desktop computer (Dimitriu & Matei, 2015). In contrast, cloud accounting delivers on-demand accounting services via the vendor’s web- based apps, accessible at any time and from any location (Christauskas & Miseviciene, 2022). Cloud computing, together with blockchain, big data analytics, and artificial intelligence (AI), has completely changed the accounting process and corporate environment in recent years (Ionescu, 2019; Wattana Viriyasitavat & Hoonsopon, 2019; Viriyasitavat et al., 2019; Yoon, 2020). Cloud accounting is the practice of managing financial transactions, reporting, and data storage using internet- based software that is housed on distant servers as opposed to a business’s local computer systems. This technology facilitates improved cooperation across organizational units, scalability, automation of repetitive accounting operations, and real-time access to financial Pa ge 14 5 https://journals.e-palli.com/home/index.php/ajfti Am. J. Financ. Technol. Innov. 3(1) 143-154, 2025 data (Adebayo & Okonkwo, 2023). Virtual accounting systems, online accounting, web accounting, e-accounting, real-time accounting, and cloud accounting software are other names for cloud accounting (Ionescu, 2019). Cloud accounting is different from traditional accounting in a number of ways, including the kind of software license (rent vs. buy), the location of the system (cloud vs. user site), and the maintenance and support costs (included in the package vs. separately purchased). The combination of the fundamentals of cloud computing and the operations of the accounting information system gave rise to cloud accounting (Khanom, 2017). Cloud accounting makes it easier to handle financial data more quickly and accurately, which is crucial for financial reporting, regulatory compliance, and strategic decision- making in the banking industry. The cloud platform facilitates the integration of various financial systems, including core banking and customer relationship management (CRM) technologies, which improves overall operational efficiency (Ibrahim & Oladele, 2022). Software Cost An organization’s financial outlay for purchasing, subscribing to, or creating accounting software applications—especially those housed on cloud platforms—is referred to as software cost. Monthly or yearly subscription fees, license fees, API integrations, and upgrades for more functionality or greater user access are common software expenses in cloud accounting. Under the cloud model, these expenses are frequently categorized as operational rather than capital costs because the majority of cloud-based technologies function as pay-as-you-use rather than one-time purchases (Okoye & Ofoegbu, 2023). Certain Nigerian banks have paid exorbitant software subscription prices without seeing a corresponding increase in the quality of their financial reporting or asset performance. A lack of connectivity with other operational tools, overlapping system functionality, or poor software vetting are frequently the causes of this gap. Software expense either increases or decreases bank profitability, depending on how well it is used. The link between cost and performance is also influenced by the kind of cloud accounting software that is used, such as Sage Cloud, Xero, QuickBooks Online, SAP Cloud, or locally created solutions (Ebere et al., 2024). The way banks handle their IT budgets and relate software expenditure to quantifiable results like profitability and operational effectiveness will be affected by this change. When software expenditures are in line with internal capabilities, they may have a substantial impact on financial performance. When properly implemented, cloud accounting solutions automate a wide range of banking tasks, including risk reporting, financial reconciliations, compliance monitoring, and real-time ledger administration. These improvements improve decision-making and asset utilization, two important factors that affect return on assets, by lowering manual processing mistakes and expediting reporting deadlines (Inegbedion et al., 2022). Training Cost Training costs are the monetary outlays made to improve staff members’ abilities, competences, and knowledge needed to effectively use cloud-based accounting systems. With the goal of maximizing user contact with cloud software, training in the context of deposit money banks includes workshops, seminars, digital onboarding sessions, certification programs, and recurring retraining. Many cloud accounting applications include sophisticated capabilities that must be continuously learned by staff members in order to be fully utilized (Inegbedion et al., 2022). The cost of training is crucial to the financial success and successful deployment of cloud accounting systems. Without proper training, even the most advanced software could be misused or underutilized, which would reduce operational effectiveness and put banks at risk for noncompliance. According to Akadi and Olaoye (2024), employees with proper training are more likely to use cloud tools efficiently, reduce input errors, produce real- time reports, and make accurate decisions—all of which improve a bank’s financial performance. In their digital migration phases, Nigerian banks that made investments in ongoing staff development reported notable gains in transaction speed, financial correctness, and risk mitigation, all of which were connected to better financial performance. These banks saw training to be an asset that facilitated performance rather than a cost. A badly designed program or one that is not in line with employee duties, on the other hand, may squander money and not produce quantifiable financial benefits (Abubakar & Bala, 2023). Conceptual Model Figure 1: Conceptual Model Source: Researchers (2025) Pa ge 14 6 https://journals.e-palli.com/home/index.php/ajfti Am. J. Financ. Technol. Innov. 3(1) 143-154, 2025 Theoretical Review Technology Acceptance Model (TAM) In 1986, Fred Davis created the Technology Acceptance Model (TAM), which was publicly published in 1989. It’s among the most popular frameworks for figuring out how people adopt and use new technologies. According to the Technology Acceptance Model, Perceived Utility (PU) and Perceived Ease of Use (PEOU) are two fundamental perceptions that influence a person’s desire to use a system and subsequently forecast actual system utilization. The degree to which an individual thinks that utilizing a certain technology will improve their performance at work is known as perceived usefulness in the context of the Technology Acceptance Model framework. How much someone thinks utilizing the system will be effortless is known as perceived ease of use. These opinions affect how users feel about utilizing the system, which in turn affects how they embrace it (Davis, 1989). Bank accountants are more inclined to embrace a cloud accounting system, for example, if they find it user- friendly and think it would improve reporting efficiency. Venkatesh and Davis (2020) claimed that the Technology Acceptance Model was expanded by include outside factors such corporate culture, user training, and system features. Its relevance in financial and accounting technology applications has been further confirmed by recent empirical research. Inegbedion et al. (2022), for instance, discovered that the adoption of cloud-based financial systems by Nigerian banks was highly impacted by perceived utility and convenience of use. Likewise, Abubakar and Bala (2023) showed that adoption rates in financial institutions are positively impacted by users’ faith in digital infrastructure, which is reinforced by training and system upgrades. But throughout the years, the Technology Acceptance Model has been criticized on a number of occasions. One significant criticism is that, because it focuses mostly on individual behavior, it has a narrow scope for explaining adoption at the organizational level. Bagozzi (2017) contended that the Technology Acceptance Model oversimplifies the many organizational and social variables that affect how people use technology. In order to capture the impact of external and environmental factors, such as cost implications, regulatory pressure, and competitive dynamics factors that are highly relevant to cloud adoption in financial institutions, others, like Legris et al. (2023), had proposed combining the Technology Acceptance Model with other theories. Additionally, the Technology Acceptance Model’s detractors point out that it ignores post- adoption behaviors that are essential to comprehending performance results, including system maintenance or long-term integration. Although the Technology Acceptance Model has limitations, it is a good supporting theory for this study, particularly when analyzing the factors that affect deposit money institutions’ acceptance and deployment of cloud accounting systems. While assessing the impact of software and training costs on financial performance is the primary focus of the study, the Technology Acceptance Model offers a behavioral perspective to comprehend the motivations behind bank investments in these domains. For instance, a high training cost may boost perceived usability, and ongoing system maintenance may raise perceived utility, which in turn may accelerate the rate of technology adoption and long-term use (Ama et al., 2025). The Technology Acceptance Model is especially useful for describing why certain banks are more successful than others at implementing cloud accounting. By capturing cost components like software and training, the model assists in connecting user-centric aspects like perceived operational advantages and ease of system learning to investment decisions. Cloud-based accounting adoption’s behavioral dimension and possible impact on performance are explained by the Technology Acceptance Model in Nigeria, where digital transformation is continuous and differs throughout institutions. Innovation Diffusion Theory (IDT) Everett Rogers developed the Innovation Diffusion Theory (IDT) in 1962 in his seminal work, titled diffusion of innovations. How, why, and how quickly new ideas and technology spread within a social system are all explained by the theory. Rogers (2003) asserts that five essential characteristics—Relative Advantage, Compatibility, Complexity, Trialability, and Observability—are necessary for an invention to be adopted. An organization like a bank’s acceptance and adoption of innovations like cloud accounting are influenced by these variables. Using the Innovation Diffusion Theory, Afolabi and Hassan (2023) explained how mobile accounting technologies were adopted by Nigerian banks, pointing out that perceived benefits and compatibility were powerful predictors of adoption. According to Igwe et al. (2022), banks that could clearly see the benefits of complete cloud integration made investments more quickly. These data support the idea that how these innovations are seen in banking contexts affects internal decisions about how much to spend on software, training, and servicing. Critics counter that the Innovation Diffusion Model largely ignores external factors like industry pressure, financial limits, and regulatory policies in favor of an excessive emphasis on organizational or individual perception. According to Lyytinen and Damsgaard (2001), the Innovation Diffusion Model fails to adequately explain post-adoption behavior, which is essential for comprehending performance outcomes following the integration of a technology. In this study, however, the Innovation Diffusion Model is still applicable as a supplementary theory that describes the cloud accounting adoption phase in deposit money institutions. Although analyzing the impact of cloud- based accounting expenses on financial performance is the study’s main goal, the Innovation Diffusion Model offers background information for comprehending how and why banks first choose to incur these expenses. Afolabi and Hassan (2023) found that banks are more likely to make major investments in software and training elements that are quantified as independent variables if they believe that cloud accounting is compatible, beneficial, and simple to deploy. Pa ge 14 7 https://journals.e-palli.com/home/index.php/ajfti Am. J. Financ. Technol. Innov. 3(1) 143-154, 2025 Empirical Review Ikwuo et al. (2025) investigated how cloud accounting might be strategically used to maximize shareholder wealth in Nigeria’s pharmaceutical industry. The study analyzed shareholder wealth using return on equity (ROE) and concentrated on two main variables: the adoption of cloud accounting software and its intensity. In order to gather secondary data from five listed pharmaceutical companies over a ten-year period (2014–2023), an ex- post facto research approach was used. Using robust least-squares regression analysis, the hypotheses were examined. Utilizing cloud accounting software increased Return on Asset in a statistically significant way (p = 0.0056), according to the data, suggesting that using cloud solutions improves shareholder returns. Nevertheless, ROE was significantly impacted negatively by cloud accounting software intensity, which indicates deeper or more complicated usage (p = 0.0147). This implies that while simple adoption has advantages, excessive expenditure or exceptionally complicated cloud solution integration may degrade the industry’s financial performance. The effect of cloud accounting on Tier 1 banks’ operational efficiency in Nigeria was examined by Enaibre et al. (2024). As crucial components of cloud technology integration, the study concentrated on cloud accounting expenses, client interfaces, and delivery methods. The capacity of the banks to efficiently offer services and optimize procedures was measured using operational efficiency as the dependent variable. In order to examine the correlations between the variables, the study used Partial Least Squares Structural Equation Modeling (PLS-SEM) using Smart-PLS 4.0. According to the findings, the client interface and delivery method had a good effect on bank performance, however cloud accounting expenses had a negative effect on operational efficiency. The associations between cloud accounting features and operational efficiency were also found to be strengthened by technological proficiency, which was an effective mediating factor. In order to achieve complete efficiency improvements, the research highlights the necessity for banks to match their internal capabilities with the deployment of technology. The impact of cloud accounting on the financial performance of Nigerian listed deposit money institutions was investigated by Daniel (2024). The study employed return on assets (ROA) to assess financial performance and computerized accounting systems (CAS) and accounting software (AS) as important indicators of cloud accounting. The study used an ex-post facto research approach and analyzed secondary data gathered from 15 listed deposit money institutions between 2013 and 2022. The study employed panel regression analysis to examine the correlation between the variables. The results showed that the financial performance of both computerized accounting systems and accounting software was positively and significantly impacted. This suggests that the use of cloud-based accounting technology improves return on assets for Nigerian listed deposit money institutions. The association between cloud accounting and organizational performance was investigated by Onyebuchukwu and Ojimini (2024) among a subset of businesses in the Port Harcourt area that used cloud accounting systems. As stand-ins for cloud accounting software, the study looked at SAP Cloud Platform and QuickBooks Online. Customer and staff satisfaction were used to gauge organizational effectiveness. The Pearson’s Product Moment Correlation (PPMC) approach was used to assess the direction and intensity of the variability-to-variable connection. The results showed that QuickBooks Online significantly increased customer satisfaction, an indication of better customer service and client involvement. Employee satisfaction was also shown to increase with SAP Cloud Platform, indicating that the platform helps improve internal operations and workflow efficiency. According to these findings, cloud accounting supports organizational performance on both an internal and external level. A study by Ezejofor et al. (2024) looked at the connection between cloud accounting expenses and Nigerian deposit money institutions’ financial results. Return on assets (ROA) was employed as a financial performance metric, and the study concentrated on two cost components related to cloud accounting: software procurement and server servicing. Ex-post facto research methodology was used, and secondary data from five publicly traded manufacturing companies was collected during an 11-year period from 2012 to 2022. Using E-Views 9.0 software, multiple regression analysis was used to examine the data. Although the cost of server maintenance improved financial performance, the effect was not statistically significant, according to the data. In contrast, the cost of software purchase had a negative and negligible impact on financial performance, indicating that investments in cloud accounting components could not result in quantifiable financial improvements for the companies under assessment right away. Onifade and Dedire (2024) examined the effect of cloud computing technology on the financial performance of Nigerian listed deposit money banks. With return on assets (ROA) as the financial success metric, the study concentrated on three essential cloud computing components: Automated Chatbot Banking Services (ACBS), Deep Learning Machines (DLM), and Machine Learning Solutions (MLS). To account for bank-level variability, the study used Panel Estimated Generalized Least Squares (EGLS) with cross-section weights and encompassed ten deposit money institutions. The findings showed that ROA was statistically unaffected by ACBS, DLM, and MLS. The results of this study indicate that although cloud-based intelligent technologies are increasingly being incorporated into banking operations, their influence on short-term financial results, such asset returns, might not yet be significant or quantifiable. Olaoye and Akadi (2024) investigated the effect of cloud-based accounting systems on the operations of a few Nigerian deposit money institutions. The Pa ge 14 8 https://journals.e-palli.com/home/index.php/ajfti Am. J. Financ. Technol. Innov. 3(1) 143-154, 2025 study looked at two aspects of cloud-based accounting systems as stand-ins for digital accounting integration: structural capital and human capital. Both financial and operational performance criteria were used to evaluate the bank’s success. Targeting all 38 deposit money banks in Nigeria, a survey research design was used. Thirty-four banks were chosen using Taro Yamane’s sample technique, however because of accessibility issues, only twenty banks ultimately took part. Of the 300 distributed questionnaires used to gather data, 279 were judged suitable for study. The findings showed that bank performance and cloud-based accounting systems were strongly positively correlated. Digital accounting plays a crucial role in improving banking operations, as evidenced by the R-value of 56.20% and R-square of 55.70%, which specifically showed that the adoption of cloud-based systems considerably explained variances in the performance of the banks under study. Ozondu et al. (2024) looked at how cloud accounting affected Nigerian deposit money institutions’ performance, specifically focusing on self-service transaction reporting (STR) and virtualized transaction reporting (VTR) as stand-ins for cloud accounting. The productivity and profitability metrics were used to measure performance. Data from a sample of Nigerian deposit money institutions was gathered using a cross- sectional survey study approach. The study’s findings showed that cloud accounting and financial success were significantly positively correlated. In particular, the banks’ operational efficiency and profitability were shown to be increased by the usage of VTR and STR, indicating that the incorporation of cloud-based reporting systems significantly improves organizational performance in the Nigerian banking industry. The impact of cloud accounting adoption on organizational performance in the domain of financial reporting among Nigerian listed corporations was investigated by Fadipe (2023). Platform as a Service (PaaS), Software as a Service (SaaS), and Infrastructure as a Service (IaaS) were the three main facets of cloud accounting adoption that were the focus of the study. The timely delivery of financial reports served as a gauge for the caliber of financial reporting. Survey research designs and ex-post facto research designs were combined. Structured questionnaires were used to collect primary data from accounting staff, while secondary data was gathered from 20 listed companies between 2010 and 2022. Regression analysis using Ordinary Least Squares (OLS) was used. Both SaaS and PaaS were found to have a noteworthy and favorable effect on the timeliness of financial reporting, demonstrating their efficacy in improving financial disclosure procedures. Nevertheless, IaaS showed no discernible impact on reporting timeliness, indicating little control over this facet of the caliber of financial reporting. Akai et al. (2023) investigated how cloud accounting affected the caliber of financial reports from a few Nigerian banks. Software as a Service (SaaS) and Infrastructure as a Service (IaaS) were utilized as stand-ins for cloud computing in this study, and the qualitative traits listed in the IASB conceptual framework were employed to gauge financial reporting quality (FRQT). Utilizing primary data gathered from 212 respondents at a few chosen banks, a survey research approach was used. Using robust Ordinary Least Squares (OLS) regression, the data were examined. The results showed that infrastructure- based cloud services significantly improve the quality of financial reporting, suggesting that they play a key role in enhancing the reliability and applicability of financial statements. While software solutions may facilitate reporting procedures, their direct influence on the caliber of financial reporting may differ throughout institutions, as seen by the positive but statistically insignificant effect that SaaS demonstrated. The fundamentals of cloud accounting information systems and their effects on Nigerian businesses’ operational efficiency were examined by Beredugo (2023). A survey research design was used for the study, and information was gathered from 385 respondents from 32 businesses in four different Nigerian economic sectors. The study concentrated on how key components of cloud accounting affect operational performance, paying special attention to how users view its implementation. The results showed that respondents’ opinions on how much cloud accounting improves operational efficiency did not differ significantly. Notably, the study raised issues with the higher danger of illegal access that comes with using cloud services. This implies that although cloud accounting could have operational advantages, adoption and adoption in Nigerian businesses are still largely dependent on concerns about data security and access control. Kpan et al. (2023) investigated the impact of cloud accounting practices on the caliber of financial data for a subset of Nigerian companies. While the accuracy, timeliness, and dependability of financial reports served as indicators of the quality of financial information, the study concentrated on data storage, data efficiency, and data mining as stand-ins for cloud accounting. Structured questionnaires were given to chosen companies as part of a cross-sectional survey study strategy. To examine the data, descriptive statistics and Ordinary Least Squares (OLS) regression were employed. The results showed that cloud accounting considerably improves the quality of financial data in every category that was assessed. Data mining (β = 0.809, p < 0.05), data efficiency (β = 0.647, p < 0.05), and data storage (β = 0.828, p < 0.05) all showed gains, suggesting that cloud technologies have a favorable impact on how financial data is processed, stored, and used in businesses. Omar et al. (2023) investigated the dangers of cloud accounting and how they affect the caliber of financial reports. To learn more about respondents’ perceptions of cloud computing’s impact on financial reporting, the study used a survey research approach. Despite concentrating on the risk aspects of cloud accounting, the Pa ge 14 9 https://journals.e-palli.com/home/index.php/ajfti Am. J. Financ. Technol. Innov. 3(1) 143-154, 2025 banks’ profitability and effective asset use were enhanced by the implementation of this cloud-based solution. The report emphasizes the strategic importance of integrated cloud technology in enhancing Nigerian commercial banks’ financial results. Since the results of the previously examined research on the financial performance of Nigerian listed deposit money banks and cloud-based accounting did not significantly agree, this study sought to advance the field by evaluating the following null hypotheses: Ho1: Software costs do not significantly affect return on assets of listed deposit money banks in Nigeria Ho2: Training cost has no significant on return on assets of listed deposit money banks in Nigeria MATERIALS AND METHODS An ex post facto research design was applied in this study. This research strategy was chosen in order to gather important data on the state of a certain phenomena during a period of naturally occurring therapy without changing the situation. Additionally, by characterizing and summarizing the data collected for the study, this design enables the researcher to give a thorough knowledge of the investigation’s objectives and contributing variables (Fleetwood, 2023). Data for this study was collected from secondary sources, specifically the annual reports and accounts of ten (10) Nigerian listed deposit money institutions. The following deposit money banks are listed: First Bank Nig. Plc., GTB Plc., Stanbic IBTC Plc., Access Bank Plc., FCMB Plc., Fidelity Bank Plc., Sterling Bank Plc., UBA Plc., and Wema Bank Plc. Furthermore, the obtained and computed data encompassed ten (10) years, from 2015 to 2024. To examine the gathered data, the study used both descriptive and inferential statistics (regression analysis and correlation). Model Specifications A model was used to look at how cloud accounting proxies affected financial performance over time. Software and training costs were used to measure cloud-based accounting costs. As a gauge of financial performance, return on assets was employed. As shown below, the study used multiple regression to evaluate the connection between the independent and dependent variables: ROA = f(SWC, TRC) ………. i The model has been formulated to suit the study as follows: ROA = α + β1SWC + β2TRC + e ……….(ii) Where; ROA = Return on Assets SWC = Software Cost TRC = Training Cost α = Constant value β1, β2 = Coefficient of Regression e = error term RESULTS AND DISCUSSION The results of the study on cloud-based accounting and study’s conclusions showed that, in principle, using cloud computing lowers storage expenses and transmission and writing mistakes. According to these results, cloud accounting may improve the overall quality and accuracy of financial statements by lowering manual mistakes and the operating expenses related to traditional accounting infrastructures, even in the face of worries about data security and system dependability. The impact of cloud accounting and related expenses on the performance of Nigerian listed manufacturing companies was investigated by Okere (2022). Utilizing a mixed-method approach that combined an ex-post facto framework with a survey research methodology, the study collected primary and secondary data to provide a thorough understanding of cloud accounting deployment in the chosen organizations. With business performance acting as the dependent variable, the study concentrated on cloud accounting adoption and costs as the independent factors. Cloud accounting and associated expenses significantly affected manufacturing enterprises’ performance, according to the research. In particular, the study showed that integrating cloud accounting systems enhanced organizational performance, even if expensive components can be problematic if they are not well matched with businesses’ cost structures. The findings highlight how adopting new technologies and controlling costs might help the Nigerian industrial sector use cloud systems more efficiently. The impact of cloud computer-based accounting on the corporate financial performance of a subset of Nigerian listed industrial enterprises was evaluated by Abidde (2021). The research used the NetSuite program as a stand-in for cloud computer-based accounting, and return on equity (ROE), return on assets (ROA), and return on capital employed (ROCE) were used to gauge the financial performance of the company. Using an ex-post facto research approach, the study covered the years 2009–2012 before adoption and 2013–2016 after adoption. The released yearly financial reports of six publicly traded industrial companies provided secondary data. According to the results, there was no statistically significant impact of NetSuite deployment on ROA, ROE, or ROCE. The financial performance metrics did not show any significant changes after adoption, despite the fact that operational efficiency was shown to increase. This suggests that the short-term operational rather than financial advantages of cloud accounting for these companies may be greater. Egbe (2020) looked at how cloud-based accounting software affected the financial performance of Nigerian commercial banks that were listed, specifically focusing on Oracle Financial Cloud usage. Key indices for evaluating financial success were return on equity (ROE) and return on assets (ROA). Only 15 quoted commercial banks were included in the study, which used a survey research approach and covered the years 2009–2016. The results showed that Oracle Financial cloud significantly affected return on equity and return on assets, indicating that the Pa ge 15 0 https://journals.e-palli.com/home/index.php/ajfti Am. J. Financ. Technol. Innov. 3(1) 143-154, 2025 financial performance of listed deposit money banks in Nigeria are shown in this section. Several robustness tests were conducted to improve the validity of the findings, in addition to trend, descriptive, correlation, and regression analysis on the collected data. Presentation of Result The descriptive data, which include the parameters’ minimum, maximum, average, standard deviation, and Jarque-Bera, are displayed in table 1 above. According to the findings, the average values for ROA, SWC, and TRC Table 1: Descriptive Results ROA SWC TRC Mean 3.143964 9.655949 8.498013 Median 1.007052 9.436273 8.507384 Maximum 127.6364 10.86541 10.13577 Minimum 0.023629 8.143015 6.446537 Std. Dev. 11.80631 0.928489 0.892629 Skewness 9.908269 -0.093733 -0.138815 Kurtosis 104.7786 1.297652 2.136351 Jarque-Bera 53757.87 14.66567 4.114840 Probability 0.000000 0.000654 0.127783 Sum 377.2756 1158.714 1019.762 Sum Sq. Dev. 16587.29 102.5889 94.81764 Observations 100 100 100 Source: E-View Output, 2025 were 3.143964, 9.655949, and 8.498013, respectively. Since SWC has a highest average value of 9.655949, compared to TRC’s 8.498013, it is clear from the average value that it is an excellent predictor of the dependent variable (ROA) among the independent variables. The variables’ maximum values were found to be 10.13577, 10.86541, and 127.6364, respectively. As an illustration, the variables’ lowest values are 0.023629, 8.143015, and 6.446537, respectively. Additionally displayed were the standard deviation numbers, which were 11.80631, 0.928489, and 0.892629, respectively. Furthermore, the study found that the probability values (0.000000 and 0.000654) of the Jarque-Bera test are less than the 0.05 significant threshold, indicating that the data gathered for ROA and SWC are not normally distributed. According to the study’s findings, the TRC data are normally distributed since the Jarque-Bera probability value (0.127783) is higher than the 0.05 significant level. The correlation results between SWC, TRC, and the adopted variable ROA are shown in Table 2 above. According to the data, SWC and TRC have a weakly positive association with ROA; their respective correlation Table 2: Correlation Analysis Correlation t-Statistic Probability ROA SWC TRC ROA 1.000000 ----- SWC 0.078507 1.000000 0.3940 ----- TRC 0.160785 0.612389 1.000000 0.0794 0.0000 ----- Source: E-View Output, 2025 values are 0.078507 and 0.160785. The p-value of 0.0000 in the preceding table can be viewed as statistically significant because it is below the 0.05 significant threshold. Consequently, the regression analysis may be conducted using the fixed effect regression model. The table below contains the previously defined coefficient for the regression model, as indicated below: ROA = 54.72383 + 7.966379SWC + 12.50473TRC The aforementioned equation demonstrates that SWC and TRC positively impact ROA, with corresponding coefficient values of 7.966379 and 12.50473. This means that the ROA of the chosen deposit money institutions will grow by 7.966379 and 12.50473 accordingly if each Pa ge 15 1 https://journals.e-palli.com/home/index.php/ajfti Am. J. Financ. Technol. Innov. 3(1) 143-154, 2025 SWC and TRC rises by one unit. Additionally displayed were the independent variables’ t-calculated values, which were 6.886906 and 3.811974, respectively. The predictors’ two t-cal values exceed the t-tab of 2. Furthermore, the 0.0002 and 0.0000 probability values that corresponded to them were displayed. Being below the 0.05 significant level, the p-values for SWC and TRC may be categorized as statistically significant. Moreover, the regression’s R-squared statistic was 0.557380, indicating that SWC and TRC account for 55.74% of the overall changes in ROA, with other parameters not used in this study accounting for the remaining 44.26%. The table above also displayed the variance analysis of the regression, with the F-statistic— which was 10.26793 with a probability value of 0.000000— as one of the important data points. It appears that the model the study created is statistically significant because the p-value is below the 0.05 cutoff. As the value is more than 1.5, the Durbin-Watson statistic result, however, was 2.390749, indicating the absence of auto-correlation. Further evidence that the study’s parameters are sound comes from here. Interpretation of Results Test of Hypotheses Ho1: Software costs do not significantly affect return on assets of listed deposit money banks in Nigeria With a matching probability value of 0.0002 and a t-cal of 3.811974 in the regression table, the SWC was deemed statistically significant as the p-value was less than the 0.05 significant threshold. As a result, the study fails ti accepts the first hypothesis stated above and affirms that software cost significantly affects return on assets of listed deposit money banks in Nigeria. Ho2: Training cost has no significant on return on assets of listed deposit money banks in Nigeria With a matching p-value of 0.0000 and a t-cal value of 6.886906 from the previously provided regression table, the training cost was considered statistically significant because it was below the 0.05 significant threshold. Thus, the study fails to accept the above-stated null hypothesis and restates that training cost has significant effect on return on assets of listed deposit money banks in Nigeria. Discussion of Findings The study investigated how listed Nigerian deposit money banks’ financial performance is affected by cloud- based accounting costs. However, the study found that while some of the empirical studies examined for this investigation had different results, others are pertinent to the findings of the study, as stated below: The study comes to the conclusion that the return on assets of listed Nigerian deposit money banks is significantly affected by cloud-based accounting, as measured by software cost. This result does support the technology acceptance model’s premise that an entity’s performance would be improved by perceived technological utility, such as cloud-based accounting. Furthermore, while the outcome is not in accordance with the findings of Enaibre et al. (2024), Ezejofor et al. (2024), and Onifade & Dedire (2024), it is in accordance with the findings of Ikwuo et al. (2025), Daniel (2024), Olaoye and Akadi (2024), Ozondu et al. (2024), and Egbe (2020). Additionally, it was demonstrated that training expenses significantly affects return on assets of Nigerian listed deposit money banks. The results also support the presumption of the technology acceptance model, which links user-centric elements like perceived operational advantages and ease of system learning to bank performance. The findings of Olaoye & Akadi Table 3: Hausman Test Test Summary Chi-Sq. Statistic Chi-Sq. d.f. Prob. Cross-section random 26.620086 2 0.0000 Source: E-View Output, 2025 Table 4: Regression Analysis (Fixed Effect) Variable Coefficient Std. Error t-Statistic Prob. C 54.72383 24.80370 2.206277 0.0295 SWC 7.966379 2.089830 3.811974 0.0002 TRC 12.50473 1.815725 6.886906 0.0000 R-squared 0.557380 Mean dependent var 3.143964 Adjusted R-squared 0.503096 S.D. dependent var 11.80631 S.E. of regression 8.322434 Akaike info criterion 7.185067 Sum squared resid 7341.868 Schwarz criterion 7.510275 Log likelihood -417.1040 Hannan-Quinn criter. 7.317135 F-statistic 10.26793 Durbin-Watson stat 2.390749 Prob(F-statistic) 0.000000 Source: E-View Output, 2025 Pa ge 15 2 https://journals.e-palli.com/home/index.php/ajfti Am. J. Financ. Technol. Innov. 3(1) 143-154, 2025 (2024), Ozondu et al. (2024), Akai et al. (2023), and Egbe (2020) are in agreement with this result; however, studies conducted by Onifade and Dedire (2024), Enaibre et al. (2024), and Ezejofor et al. (2024) do not support it. CONCLUSION In line with the research findings, the study concludes as follows: Regression table results showed that software cost has a significant impact on return on assets of Nigerian listed deposit money banks, and the study concludes that software cost has a significant impact on return on assets of Nigerian listed deposit money banks and can therefore be used to predict return on assets of the chosen banks. The results also showed that the return on assets of Nigerian listed deposit money banks is significantly affected by training costs. Furthermore, the results showed that the return on assets of Nigerian listed deposit money institutions is significantly impacted by training costs. The study comes to the conclusion that as training costs have a favorable impact on the return on assets of Nigerian listed deposit money banks, their importance in influencing return on assets cannot be overstated. Recommendations The underlisted recommendations were made in accordance to the findings and conclusion of the study: Nigerian listed deposit money banks should increase their investment in accounting software as it’s a creative strategy to increase their return on assets and provide them a competitive edge over rivals. The study concluded that the cost of training has a major impact on the financial performance of Nigerian deposit money banks. As a result, it is therefore suggested that the Nigerian government, trade associations, and financial institutions give training and skill development in technology infrastructure top priority in order to facilitate the broad implementation of cloud-based accounting in Nigerian deposit money banks. REFERENCES Abdulmunim, O. (2018). Cloud accounting in Jordanian public shareholding companies: The role of internal audit. Corporate Ownership & Control, 15(4), 158–164. Abidde, M. O. (2021). 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