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ARTIFICIAL INTELLIGENCE AND ACCOUNTING PROFESSION
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BABCOCK JOURNAL OF ACCOUNTING AND FINANCE
Vol 1, No 1
April 2021
pp. 1-26
ISSN 2795-353X
ARTIFICIAL INTELLIGENCE AND
ACCOUNTING PROFESSION
KWARBAI Jerry D. and OMOJOYE Elizabeth O.
Babcock University, Accounting department, Nigeria
ABSTRACT
The study investigated the effect of artificial intelligence and accounting profession in
Nigeria. The study employed a field survey research design. The population of this study
are accountants in Nigeria considering the Big Four which include KPMG, Deloitte,
PricewaterhouseCoopers and Ernst and Young. The study found that Artificial
Intelligence had significant accounting profession in Nigeria. The study recommended
that accounting software of assurance firm should learn from previous tagging decisions
that are typically made according to rules that the accountant is aware of and also
integrate artificial intelligence into their system of sampling in case an audit is required,
it will be possible to audit all the data rather than merely a sampling.
Keywords- Accounting Profession, Artificial Intelligence, Anomalous Detection, Data
Analytics, Anomalous Detection
1. INTRODUCTION
According to the American Accounting Association, accounting is the process of identifying,
measuring, and communicating economic information to influence the decisions of the users of the
information. As outlined by the Association of Chartered Certified Accountants in 2016, the
accountancy profession serves as the backbone for shaping and supporting businesses,
organizations, and global economies. According to Kaidonis (2008), the accounting profession plays
a role in every facet of the economy ranging from the serving both states and individual interest.
Jindrichovska and Kubickova (2016) also observed that qualified accounting professionals acts in
different capacities within an organization, providing book keeping and reporting services and also
specializing in cost accounting, internal where necessary. Furthermore, they asserted that smallsized organizations outsource their accounting functions to external accounting firms.
Uche, (2002) views professional associations as a largely political bodies whose purpose is to define,
organize, protect and advance the interest of their members. As stated by Kaidonis (2008), the
accounting profession is an important facet of our society and as such influences the broader society
at largely, thus deemed to be socially constructive. She also highlighted the role of the accounting
standards at averting potential adverse economic issues and ultimate politicization of the
accounting profession.
Artificial Intelligence is an umbrella term covering machine learning, deep learning, speech
Submitted: January 2021
Accepted: March 2021
1Published Online: April 2021
78
Enterprise Risk Management And Corporate Performance Of Insurance Firms In Nigeria
79
recognition and cognitive computing, which are not new concepts. In fact, the elements of AI work
together to discover complex patterns and provide automated insights drawn from the increasing
amounts of data to which organisations have access (CGMA, 2019). Within the AI space, the main
debate across organizations from all sectors and industries is this will the technology lead to
augmented human intelligence, or will it lead to the rise of autonomous intelligence and machine
automation (CGMA, 2019). Furthermore, AI facilitates speedy delivery of information. The
development of modern computers that has powered the artificial intelligence in applying the
methods of self-management, self-tuning, self-configuration, self-diagnosis, and self-healing to
achieve optimum result in accounting operations. (Odoh,, Echefu, Ugwuanyi, & Chukwuani 2018).
With the improvement and advancement in these technologies, artificial intelligence has eaten deep
into the profession, consequently posing a risk to the relevance of the accounting profession. It is
necessary that businesses maintain their competitive advantage by constantly seeking to develop
and achieve optimal efficiency. However, as outlined in Greenman (2017), he noted that as
technology advances, some jobs are eliminated while others are created as artificial intelligence
assists in reducing rigorous, tedious and painstaking nature of accounting profession and
consequently making other accounting processes more efficient and reliable. In contrast to the
notion proposed by Greeman (2017). Odoh et al., (2018), observed that the greatest danger of
Artificial Intelligence involves ignorance on the part of individuals professing complete
understanding of AI, whereas otherwise. According to research undertaken by the University of
Oxford in 2015, accountants have a 95 percent chance of losing their jobs in the light of recent
technological revolution. On the back of this, accountants and employees are required to seek and
aid relevant skill gathering to aid the adaption to recent technological evolution.
The recent technological breakthroughs in AI are now opening a new page in accounting discipline
refocusing the research from ESs applications to some new perspectives towards accounting
practitioners: how could accountants benefit from the use of AI capabilities? What is the long-term
vision for AI and accountancy? (ICAEW 2018). This new generation of machine learning systems have
great impact on economics and business but they are also bringing new life style and sociological
side effects. (Stancheva-Todorova, 2018). Drilling down the emergence of artificial intelligence in the
accounting profession, we note that this emergence has resulted in a more efficient and reliable
accounting processes, although posing immense threats to accounting practitioners. Given the
instantaneous processing and retrieval ability provided by artificial intelligence, there are rising
concerns of a potential replacement of human capital by technologies. Concentrating on the
potential impact of artificial intelligence on the accounting profession, this research work seek to
analyze and evaluate the opportunities and challenges posed by artificial intelligence on the
accounting profession
The history of AI applications in the accounting domain could be traced back to the 1980s. An
extensive research was conducted by academics and practitioners on AI application in auditing,
taxation, financial accounting, management accounting and personal financial planning. Expert
Systems, considered as software programs attempting to replicate human experts’ behaviour and
expertise, store human knowledge and experience and transform it into rules thus trying to solve
accounting problems and perform some accounting tasks. Some Expert Systems have been
developed for analysis of accounting-based decision processes (Stancheva-Todorova, 2018).
Thus, the main objective of this study is to investigate the effect of artificial intelligence and
accounting profession in Nigeria. The specific objectives of the study are to Identify the extent to
which artificial intelligence will efficiently improve the reporting accuracy of accounting
professionals, Identify the extent to which artificial intelligence will conductively promote
transparent reporting of accounting professional and to examine the efficiency of artificial
intelligence in data analytics of an accounting professional. The remainder of the paper is organized
as follows: section 2 provides a review of related literatures; section 3 describes the methodology of
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the research; section 4 shows the result of the analysis and its discussion; and section 5 provides the
conclusion for the study.
2. Related literature review and hypothesis development
2.1
ARTIFICIAL INTELLIGENCE
Artificial Intelligence is systems that are programmed to think and work as human intelligence does
things better than humans through the experimental aspect of computer science involved in
programming an intelligent machine that can operate on various tasks by using its intelligence
(Dongre, Pandey, & Gupta, 2020). In the same light, Ezeribe, (2019) viewed Artificial Intelligence as a
method of making a computer, a computer-controlled robot, or software think intelligently like the
human mind. Odoh, et al (2018) also described artificial intelligence as a program that has the ability
of software to carry out activities which only the human brain is expected to carry out. These
activities include the capacity for knowledge and the ability to acquire it. It also comprises the ability
to judge, understand relationships and produce original thoughts.
In another perspective, Artificial intelligence is the ability of a computer system to be able to observe
and learn from its experiences and simulate human intelligence in decision-making (Ezeribe, 2019).
Artificial intelligence recognized as software programs that attempts to copy human experts’
behaviour and expertise and then store human knowledge and experience and transform it into
commands it uses to solve accounting problems and perform some accounting tasks (StanchevaTodorova, 2018). He also noted that Artificial intelligence aims to make an intelligent machine that
can react in ways similar to humans. It also comprises the ability to judge, understand relationships,
and produce original thoughts.AI is rapidly changing how the financial organization operated
functions and increased operational efficiency level with the minimum efforts (Odoh et al., 2018).
The difference between artificial intelligence and other developing technologies is its ability to
understand its environment and perform tasks that normally require human intelligence in only a
relatively short time (PWC, 2019). In essence, Artificial intelligence is similar to the simulation of the
human brain’s thinking and information processes, the human thinking simulation can be carried
out in two ways. The First is the structural simulation can imitate
2.2 ACCOUNTING PROFESSION
In the need to make prudent use of scarce resources, gather wealth and produce high quality of
goods and services in a competitive economy, birthed the need for accounting profession. In simple
terms, accounting profession is seen as a profession that is responsible collecting, classifying, and
recording, summarizing, analyzing and interpreting of information to users of financial statement.
Accounting profession provides qualitative financial information about economic entities that is
intended to be useful in economic decisions. This information allows users to make reasoned
choices among alternative uses of scarce resources in the conduct of business and economic
activities.
Professional Accountants are people who trained as accountants and also obtained an additional
training from the recognized professional accounting bodies. These professional accounting bodies
award them recognition and licensed them to execute accounting and financial services to the public.
The accounting bodies monitor and supervise them frequently to ensure strict adherence to the
principles of best practice and ethical considerations. According to Ronny & Yuanyuan (2013) the
skills required by an accountant are Language skills, computer skills, interpersonal skills, leadership
skills, analytical skills, multi-task skills, due diligence skills, and training skills. The same light,
several knowledges required by accounting profession include are accounting, auditing, taxation,
accounting software, business law, human resource management, retail/consignment business,
operation & supply chain, project management, and strategic management. Ronny & Yuanyuan
Babcock Journal of Accounting and Finance
Volume 1, Number 1, 2021
Enterprise Risk Management And Corporate Performance Of Insurance Firms In Nigeria
81
(2013) identified the process of accounting as the preparation of financial reports starting from
documents till financial statements. He indicated three aspects of accounting process including
Designing, preparing, and handling accounting process.
2.3. THEORETICAL REVIEW
2.3.1 AGENCY THEORY
The agency theory has its beginning in economic theory. This was made by Alchian & Demsetz (1972)
and further developed by Jensen and Meckling (1976). In the agency theory, the principal (owners
and shareholders) makes the decision-making power to the agent (directors, managers and
management) who may pursue interests that may not necessarily be in favor of the principal but may
in fact hurt the principal through information asymmetry (Ogoun, 2020). The agency theory deals
with entrusting products to the agent who in turn is required to produce a statement in qualitative
and quantitative way and are expected to be in alignment with the interest of the owners of a
business and managers of a business and managers in order for the set objectives of the
organization to be achieved.
Basic agency paradigm was made in the economics literature during 1960s and 1970s in order to
determine the optimal value of the risk- sharing among different individuals (Jensen & Meckling,
1976). However, gradually the agency theory domain was extended to the management area for
determining the cooperation between various individuals with different objectives in the firm, and
goal congruency attainment (Kwafo, 2019). In 1980s, agency theory was also appeared extensively in
the auditing and accounting realms to determine the optimal-incentive contracting among different
people and suitable accounting control mechanisms establishment for monitoring of their behaviors
and actions (Gotthardt, et al., 2020). It is this last function of the agency theory that will be
emphasized in this study. In its primitive form, agency theory relates to situations in which one
individual (called the agent) is engaged by another person (called the principal) to perform on
his/her behalf based upon a designated compensation schedule. Since both persons are assumed to
be utility maximizer, and motivated by pecuniary and non-pecuniary items, incentive problems may
come up, particularly under the condition of uncertainty and informational asymmetry (Longinus,
2018). That is, the objective function of the principal and the agent may be incompatible, and
therefore, the agent may take acts which will be different from the principal's benefits. Hence, we
posit that:
There is no significant relationship between artificial intelligence and reporting accuracy in Nigeria.
There is no significant relationship between artificial intelligence and transparent reporting in
Nigeria.
There is no significant relationship between artificial intelligence and data analytics in Nigeria.
RESEARCH METHODOLOGY
3. RESEARCH DESIGN
The research design used for this study is the survey research design. This design is deemed most
suitable as it will allow seeking the opinions of well-informed individuals on the influence of
artificial intelligence on accounting profession in Nigeria, which will provide comprehensive
thoughts from the number of individual cases.
3.1 Data collection and research variable
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The study used a descriptive field survey research design and adapted questionnaire as a research
instrument. The population of the study was the big 4 operating in Nigeria. 500 questionnaire
instruments were distributed evenly across the firms but only 277 were correctly completed and
returned. Multiple regression analysis was used to determine the cause-effect of the independent
variables on the dependent variable. Analysis was done with the aid of Statistical Package for Social
Sciences (SPSS 23.0). The questionnaire consists of three sections, sections; A, B and C. Section A
focused on the demographic information of the respondents covering; the gender, marital status,
educational qualification, professional qualification and experience on the job. Section B focused on
artificial intelligence on test automation, anomalous errors and predictive forecasting solutions.
And section C, accounting profession on reporting accuracy, transparent reporting and data
analytics. The instrument was structured using the four point rating Likert scale comprising of
Strongly Agree (SA), Agree (A), Disagree (D), and Strongly Disagree (SD) from which the respondent
specified their level of agreement
3.2 Model specification and estimation technique
The regression equations are given as:
RA = β0 + β1TA +β2AD +β3PFS + µ1
TS = β0 + β1TA +β2AD +β3PFS + µ2
DA = β0 + β1TA +β2AD +β3PFS + µ3
Where: α0 = constant or intercept, this is the average value of the dependent variable when the
independent variable is equal to zero
β = regression parameter, which measures the coefficient.
µi= error term or stochastic variable.
The estimated model result is shown in the table below:
Table 1: Summary Empirical Analysis
Parameters
Hypothesis 1
Coeff
SE
Hypothesis 2
T-Stat
P-value
Coeff
SE
Hypothesis 3
T-Stat
P-
Coeff
SE
value
5.75
Constant
AT
AD
PFS
.858
6.703
.000
.315
.074
4.260
.000
.019
.063
.310
.334
.073
4.557
4
5.20
7.40
.949
5.488
.000
.274
.082
3.361
.001
.234
.077
.757
.188
.070
2.708
.007
.171
.065
.000
.220
.081
2.716
.007
.155
.076
8
0
.891
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Enterprise Risk Management And Corporate Performance Of Insurance Firms In Nigeria
Model Summary
Adjusted
R
Model
R
R Square
1
.633a
.401
.394
.000b
2
.592a
.350
.343
.000b
3
.541a
.292
.284
.000b
Square
Sig.
Author’s computation of Field Survey Data (2021) using SPSS version 23
4.3.1 EMPIRICAL ANALYSIS OF MODEL ONE
The estimated model in the table above is given as: RA = 5.754+ 0. .315AT + 0.019AD + 0.334PFS + µ
Table 1 shows the analysis result of model 1, the result indicates that automation tagging,
anomalous detection and predictive and forecasting solution all exerted a positive effect on
reporting accuracy. This is indicated by the signs of the coefficient β1=0.315, β2=0.019, β3=0.334
respectively. The result also showed that automation tagging and predictive and forecasting
solution significantly effects reporting accuracy this is constant with unstandardized coefficients
because it exceeded AI proxy by automation tagging, anomalous detection and predictive and
forecasting solution should have a positive and significant effect on reporting accuracy. The result
implies that a percentage change in automation tagging, anomalous detection and predictive and
forecasting solution will bring about 0.315, 0.019, 0.334 respective increase in reporting accuracy
Furthermore, the adjusted R squared is 0.394 implying that 39% change in reporting accuracy is
brought about by a change in AI while 61%was not factored in the model
4.3.2 Empirical Analysis of Model Two
The estimated model in the table above is given as: TS = 5.208+ 0.274AT + 0.188AD + 0.220PFS + µ
Table 4.3.2 is the analysis result of model 2, the result indicates that automation tagging, anomalous
detection and predictive and forecasting solution all exerted a positive effect on reporting accuracy.
This is indicated by the signs of the coefficient β1=0.274, β2=0.188, β3=0. 220 respectively. The result
also showed that automation tagging, anomalous detection and predictive and forecasting solution
significantly effects reporting accuracy this is constant with the p-value of the variable of AI proxy
indicated by automation tagging, anomalous detection and predictive and forecasting solution
which have a positive and significant effect on reporting accuracy. The result implies that a
percentage change in automation tagging, anomalous detection and predictive and forecasting
solution will bring about 0.274, 0.188, 0. 220 respective increases in reporting accuracy.
Furthermore, the adjusted R squared is 0.343 implying that 34% change in reporting accuracy is
brought about by a change in AI while 66%was not factored in the model
4.3.3 Empirical Analysis of Model Three
The estimated model in the table above is given as: DA = 7.400 + 0 .234AT + 0 .171AD + 0.155PFS + µ
Table 1 shows the analysis result of model 3, the result indicates that automation tagging,
anomalous detection and predictive and forecasting solution all exerted a positive effect on
reporting accuracy. This is indicated by the signs of the coefficient β1=0234, β2=0.171, β3=0.155
respectively. The result also showed that automation tagging and predictive and forecasting
Babcock Journal of Accounting and Finance
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Kwarbai and Omojoye
84
solution significantly effects reporting accuracy this is constant with unstandardized coefficients
because it exceeded AI proxy by automation tagging, anomalous detection and predictive and
forecasting solution should have a positive and significant effect on reporting accuracy. The result
implies that a percentage change in automation tagging, anomalous detection and predictive and
forecasting solution will bring about 0234, 0.171, 0.155 respective increase in reporting accuracy
Furthermore, the adjusted R squared is 0.284 implying that 28% change in reporting accuracy is
brought about by a change in AI while 72% was not factored in the model
4.4. DISCUSSION OF FINDINGS
Model one showed that Automation Tagging, Anomalous Detection and Predictive forecasting
solution have positive significant effects on Reporting Accuracy. Other than Artificial Intelligence,
Reporting Accuracy is predicted by other factors, being associated with a correlation coefficient of
0.633. It also explains about 39% of shifts in Reporting Accuracy caused by Artificial Intelligence.
Artificial Intelligence has a significant impact on reporting accuracy in respect to accounting
profession banks in Nigeria. The outcome is in line with the work of Ukpong, Udoh and Essien (2019),
which studied the Opportunities, Issues and Applications of Artificial Intelligence in Accounting and
Auditing in Nigeria and stated that AI integration will facilitate changes in the auditing process.
Similarly, the studies of Odoh, Silas, Ugwuanyi, and Chukwuani (2018) stated there is a strong
positive relationship between intelligent agent and the performance of accounting functions.
The study of Longinus (2018) explored the implication of artificial intelligence system for proper
record keeping in Microfinance Banks in Nigeria. The result shows that there is strong positive
relationship between artificial intelligence system and proper record keeping. The findings
contradicted the findings by Mohammad (2012) and Jessie (2019) that stated that automation
tagging, Anomalous Detection and Predictive and forecasting solution have no effect on customer
satisfaction. The empirical analysis of model two showed that Automation Tagging, Anomalous
Detection and Predictive forecasting solution have positive significant effects on Transparent
Reporting. Other than Artificial Intelligence, Transparent Reporting is predicted by other factors,
being associated with a correlation coefficient of 0.592. It also explains about 34% of shifts in
Transparent Reporting caused by financial Artificial Intelligence. Artificial Intelligence has a
significant impact on Transparent Reporting as regards to Accounting Profession in Nigeria. This
finding is consistent with the work of Jooman (2019), studied the influence of artificial intelligence
on the future of the internal auditing profession in South Africa. The research findings suggested
that the current influence of AI on the internal auditing profession within the SA context is still in its
infancy and internal auditors do not yet understand and appreciate the capabilities of AI. Also,
Mhlanga (2020), studied The Impact of Artificial Intelligence (AI) on Digital, and it was discovered
that The result of the study showed that Artificial Intelligence has a strong influence on digital
financial inclusion in areas related to risk detection, measurement and management, addressing the
problem of information asymmetry, availing customer support and helpdesk through catboats and
fraud detection and cyber security. The findings contradicted the result of Ozili (2018). In addition,
the findings of Model three, as predicted, have shown that Automation Tagging, Anomalous
Detection and Predictive forecasting solution have positive significant effects on Data Analytics.
Other than artificial intelligence, Data Analytics are predicted by other factors, being associated with
a correlation coefficient of 0.541. It also explains about 28% of shifts in data analytics caused by
artificial intelligence. Artificial Intelligence has a significant impact on Data analytics in respect to
Accounting Profession in Nigeria.
The study by Ogoun (2020) conducted a reviewed on Expanding the Frontiers of Accounting
Knowledge on Imperative for Practitioners Accommodation. It revealed for as long as practitioners
foreclose new knowledge deployment, a consummate expansion of the accounting knowledge base
cannot be actualized. Accounting would continue to blaze the backward-trail in new knowledge
Babcock Journal of Accounting and Finance
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Enterprise Risk Management And Corporate Performance Of Insurance Firms In Nigeria
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development, relative to other academic disciplines and professional practice. Also, Duong and
Fledsberg (2019) stated reviled that accountants understanding of digitalization, are in the early
stage of the digitalization process, the importance of having technical skills in order to enter the new
role, the self-understanding of accountants. The findings also revealed that the findings the
accountant is expected to have other qualities such as being an IT-expert, outgoing, and openminded. The study of Dongre, Pandey and Gupta (2020) revealed that the use of AI applications will
make the work of the accountant more valuable, rather than stay in simple accounting work. The use
of AI in accounting increases analytical capability and decision-making ability.
CONCLUSION AND RECOMMENDATION
The result of all the analysis carried out revealed that Artificial Intelligence has positive significant
effect on Reporting Accuracy, Anomalous Detection and Data Analytics in respect to accounting
profession in Nigeria. However, based on level of significance, it can be concluded that artificial
intelligence is significant to an improved system in the accounting profession.
The study recommended that:
Based on the findings of this study, it is therefore recommended that:
1.Accounting software of assurance firm should learn from previous tagging decisions that are
typically made according to rules that the accountant is aware of. In years to come, the ability of
technology to discover these rules and predictively plan will help to remove a significant component
of the firms’ daily workload
2.Assurance firms should integrate artificial intelligence into their system of sampling. Incase an
audit is required, it will be possible to audit all the data rather than merely a sample, yet without the
huge resources typically required for what’s traditionally considered a full audit. It will be able to
discover anomalies that may exist, and the process will be much quicker and take significantly less
effort.
3.Management of assurance firms should integrate artificial intelligence into their system, as this
will help foster a closer and more useful relationship with your clients.
Suggestion for further study was prompted from the limitations of this study. Further studies may
be carried out in the following areas. The research is based mostly on accounting profession with
case study consideration on assurance and consultancy firms; further studies could be carried out
on other types of companies in other sectors listed on the NSE. Further studies can be extended to
more years. Comparison of different sectors in Nigeria can also be considered.
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REFERENCES
Alchian, A., and Demstez, H., (1972) Production, Information Costs, and Economic Organization, 62
America Economic 7
Baldwin, AA, Brown, CE & Trinkle BS 2006, Opportunities for artificial intelligence development in
the accounting domain: the case for auditing’, Intelligent Systems in Accounting, Finance and
management. 14
CGMA, (2019). Re-inventing finance for a digital world. Association of International Certified
Professional Accountants 1901-0243 ISBN: 978-1-85971-871-1
Dilek, S.; Çakır, H. & Aydın, M. (2015). Applications of artificial intelligence techniques to combating
cyber-crimes: A review. International Journal of Artificial Intelligence & Applications (IJAIA).
6(1).
Dongre .N., Pandey .A. & Gupta O. P(2020). Artificial Intelligence in Accounting: Opportunities &
Challenges. Journal of Xi'an University of Architecture & Technology. ISSN No: 1006-7930
7(5),
Duong .D.C.T. & Fledsberg .K. (2018) Digitalization of the Accounting Industry The influence of
digitalization on the accountants’ role and their self-understanding - An exploratory study
based on 13 Norwegian accounting firms
Ezeribe .C (2019).
Artificial Intelligence (AI) and the Accountancy Profession: The Threats Of
Obsolescence
Gotthardt .M., Koivulaakso .D., Paksoy .O., Saramo .C., Martikainen .M., Lehner .O. (2020) Current
State and Challenges in the Implementation of Smart Robotic Process Automation in
Accounting and Auditing ACRN Journal of Finance and Risk Perspectives 9
Graetz, G., and Michaels, G. (2015). Estimating the impact of robots on productivity and employment.
Center for Economics and performance.
Greenman, C. (2017). Exploring the impact of artificial intelligence on the accounting profession.
Journal of Research in Business, Economics and Management (JRBEM).
Griffin, O. (2016). How artificial intelligence will impact accounting.
ICAEW 2018 Artificial Intelligence And The Future Of Accountancy ISBN 978-1-78363-816-1
TECPLN16345 09/18
Imene .F. & Imhanzenobe .J. (2020). Information technology and the accountant today: What has
really changed? Journal of Accounting and Taxation DOI: 10.5897/JAT2019.0358.
Babcock Journal of Accounting and Finance
Volume 1, Number 1, 2021
Enterprise Risk Management And Corporate Performance Of Insurance Firms In Nigeria
97
0F5E6B663319, ISSN 2141-6664 12(1).
Jensen, M. C., and Meckling, W. H. (1976), Theory of the Firm: Managerial Behaviour, Agency Costs
and Ownership Structure, 3 Journal of Financial Economics 305.
Jooman,.S. (2019)
The influence of artificial intelligence on the future of the internal auditing
profession in South Africa. WBS/BA0407882V/993
Kaidonis, M. (2008). The Accounting Profession: Serving the public interest or capital interest?
Australasian Accounting Business and Finance Journal, 2(4).
Kaplan, R. S. and Norton, D.P. (1992), The Balanced Scorecard: Measures that Drive Performance,
Harvard Business Review, 70, 71-79
Kaplan, R. S., and Narayanan, V. G. (2001), Measuring and managing customer profitability. Journal
of Cost Management, (September/October), 5-15
Kaplan, R.S. (1984), The Evolution of Management Accounting, Accounting Review, 59(3), 390 – 418
Kaplan, R.S. (1994), Management accounting 1984-1994: development of new practice and theory,
Management Accounting Research, 5(3/4).
Kaplan, R.S. and Norton, D.P. (1996), the Balanced Scorecard: Translating Strategy into Action,
Boston MA: Harvard Business School Press.
Kokina .J. & Davenport .T.H. (2017) The Emergence of Artificial Intelligence: How Automation is
Changing Auditing. Journal of Emerging technologies In Accounting American Accounting
Association Vol. 14, No. 1 DOI: 10.2308/jeta-51730 Spring 2017 pp. 115–122
Kwafo .D. (2019) The Impacts of Artificial Intelligence on Management Accounting Students: A Case
Study At Oulu Business School, University Of Oulu
Longinus, O. (2018). Artificial Intelligence System: Implication for Proper Record Keeping in
Microfinance Banks in Nigeria, International Journal of Academic Research in Accounting,
Finance and Management Sciences, 8 (1): http://dx.doi.org/10.6007/IJARAFMS/v8-i1/3926
Luo, Meng & Cai, (2018). Analysis of the impact of artificial intelligence application on the
development of accounting industry, Open journal of business management. 6.
Mhlanga .D. (2020).Industry 4.0 in Finance: The Impact of Artificial Intelligence (AI) on Digital
Financial Inclusion. International Journal of Financial Studies, 8, 45;
doi:10.3390/ijfs8030045.
Odoh, L.C, Echefu S.C, Ugwuanyi, U.B & Chukwuani N.V. (2018). Effect of Artificial Intelligence on the
Performance of Accounting Operations among Accounting Firms in South East Nigeria Asian
Babcock Journal of Accounting and Finance
Volume 1, Number 1, 2021
Kwarbai and Omojoye
88
Journal of Economics, Business and Accounting 7(2): 1-11, 2018; Article no.AJEBA.41641
ISSN: 2456-639X
Ogoun .S. (2020). Towards Expanding the Frontiers of Accounting Knowledge: Imperative for
Practitioners Accommodation. Journal of Finance and Accounting. Vol. 8, No. 2, 2020, pp. 7382. doi: 10.11648/j.jfa.20200802.13
Omoteso, K. (2012). The application of artificial intelligence in auditing: Looking back to the future.
Expert Systems with Applications, 39(9), 8490-8495.
PWC (2019). How Tax is leveraging AI —including machine learning —in 2019.
Rogers, E. M. (1995). Diffusion of Innovation. 4th. New York: The Free Press.
Rogers, E. M. (2003). The diffusion of innovation 5th edition.
Schumpeter, J. A. (1934), The Theory of Economic Development: An Inquiry into Profits, Capital,
Credit, Interest and the Business Cycle, London: Oxford University Press.
Stancheva-Todorova E.P (2018). How Artificial Intelligence Is Challenging Accounting Profession.
Journal of International Scientific Publications 1314-7242, Volume 12
Uche, CU (2002), Professional accounting development in Nigeria: threats from the inside and
outside, Accounting, Organizations and Society, 27(4-5).
Ukpong EG, Udoh II, Essien IT (2019) Artificial Intelligence: Opportunities, Issues and Applications in
Accounting and Auditing in Nigeria. J Account Mark 7(309). doi: 10.4172/2168-9601.1000309
Yadav, A., Gupta, V., Sahu, H., and Shrimal, S. (2017). Artificial intelligence – new era. International
Journal of New Technology, 3(3).
Zehong, L. & Zheng, L. The Impact of Artificial Intelligence on Accounting Advances in Social Science.
Education and Humanities Research (ASSEHR), 181
Babcock Journal of Accounting and Finance
Volume 1, Number 1, 2021
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