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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



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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 



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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)



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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.



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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 



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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 



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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 



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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 



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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



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(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.

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