Application of Artificial Intelligence and Audit Quality in Nigeria

The significance to prepare reliable information discloses the need to fall back on an external auditor and a quality auditing process that can caution against the management of earnings. In line with the business practice, auditing does not provide sufficient coverage for some earnings management (EM) activities that result in financial statement fraud. Over the years, capital markets around the globe have witnessed numerous corporate financial scandals largely because of financial and accounting figures' manipulation. This has led to casting doubt on the quality of published financial reports and questioning the ability of the audit process. Against this background, this study examined the relationship between audit quality and real earnings management of listed manufacturing companies in Nigeria. Specifically, this study evaluated the effect of audit firm size, audit firm industry specialization, audit firm tenure, and audit firm independence on real earnings management. The study sampled 38 out of 55 listed manufacturing companies that cut-across different sectors from 2013 to 2020. From the multivariate analysis, the findings revealed a significant relationship between audit quality (audit firm size and audit firm independence) with a p-value of 0.014 and 0.003 respectively. It was concluded that firms audited by Big-4 firms with independence attract greater publicity and tighter scrutiny; hence, companies tend to desist from managing their earnings. The study, therefore, recommended that the management of manufacturing firms in Nigeria should persist in engaging experience audit firms with international affiliations, and they should work strictly with the CAMA, 2020 as amended by rotating audit firms after every three years as this will promote the reliability of financial statement prepared by management, and finally reduce manipulation of earnings.

This study aims to empirically examine the effect of auditors’ independence, audit tenureship, firm characteristics on audit quality in Nigeria. The population of the study comprises a sample of ten (10) listed pharmaceutical companies listed on the Nigerian Exchange Group (NGX). The time period for the study covers audited financial statements of the companies from 2013-2019. The study focused on two explanatory variables: auditors’ independence and audit tenure, and two control variables: firm size and firm age. While the dependent variable audit quality was proxied by big four firms and non-big four firms. The secondary source of data was adopted in this study. The data collected were analyzed using the panel regression techniques. The results suggest that all of the explanatory and control variables have a positive and significant effect on audit quality. The study recommends that auditors’ independence is directly proportional to audit quality, thus audit firms should be independent in order to enhance audit quality. Auditor-client engagement should not exceed 3years in order to avoid familiarity threat. In addition, firms are advised to engage the services of one of the big audit firms since it results to improved audit quality. Younger firms should understudy older firms to learn from the experiences that they have acquired over the years that impact positively on audit quality.

The purpose of this study is to find out the perception of professional accountants in Nigeria on how some cultural factors affect audit quality. A survey research design was adopted for the study. A questionnaire survey of 108 professional accountants was undertaken. Descriptive statistics were used to analyze the 50 usable responses received. The one sample t-test was used to confirm the significance of the responses. Findings include the fact that some Nigerian accountants receive bribes in the course of duty thus compromising audit quality. Also low litigation culture, slow and tardy judicial process and corruption in the wider Nigerian Society affected adversely audit quality. Our findings have implication for the regulatory authorities as they strive to rein in the monster of audit failures and thus improve audit quality in Nigeria.

Does International Accounting Network Membership Affect Audit Fees and Audit Quality? Evidence From China

This study investigates the scientific development of Artificial Intelligence (AI) and Machine Learning (ML) applications in Human Resource Management (HRM) through bibliometric analysis. To this end, 522 academic publications indexed in the Scopus database between 2020 and 2024 were analyzed using the R-based bibliometrix package and VOSviewer software. Descriptive analysis, scientific productivity metrics, and content analysis techniques were employed. The findings revealed three main patterns. First, research on AI and ML applications in HRM has grown significantly—particularly between 2022 and 2024—driven by post-pandemic digital transformation. Second, India, China, and the USA lead in research output, while the UK and France demonstrate strong citation impact, indicating a globally expanding research ecosystem. Third, the thematic focus of research is shifting from technical infrastructure toward more human-centered and ethical dimensions. Additionally, keyword co-occurrence network analysis identified three major thematic clusters: HRM functions, AI applications, and machine learning analytics, highlighting the field’s interdisciplinary nature. Compared to the previous studies, this research provides a more comprehensive bibliometric analysis of AI and ML applications in HRM. It is the first extensive study to map the intellectual evolution of the field from a multidisciplinary perspective. Furthermore, it charts research trends and collaboration networks, revealing a shift from technical implementations to strategic integration. In conclusion, this analysis offers new insights to the literature by illustrating the technological evolution in HRM and highlighting the growing significance of cutting-edge approaches such as AI and ML, reaffirming the field as a timely and impactful area of research.

Machine Learning (ML) algorithms, as the core technology in Artificial Intelligence (AI) applications, such as self-driving vehicles, make important decisions by performing a variety of data classification or prediction tasks. Attacks on data or algorithms in AI applications can lead to misclassification or misprediction, which can fail the applications. For each dataset separately, the parameters of ML algorithms should be tuned to reach a desirable classification or prediction accuracy. Typically, ML experts tune the parameters empirically, which can be time consuming and does not guarantee the optimal result. To this end, some research suggests an analytical approach to tune the ML parameters for maximum accuracy. However, none of the works consider the ML performance under attack in their tuning process. This paper proposes an analytical framework for tuning the ML parameters to be secure against attacks, while keeping its accuracy high. The framework finds the optimal set of parameters by defining a novel objective function, which takes into account the test results of both ML accuracy and its security against attacks. For validating the framework, an AI application is implemented to recognize whether a subject's eyes are open or closed, by applying k-Nearest Neighbors (kNN) algorithm on her Electroencephalogram (EEG) signals. In this application, the number of neighbors (k) and the distance metric type, as the two main parameters of kNN, are chosen for tuning. The input data perturbation attack, as one of the most common attacks on ML algorithms, is used for testing the security of the application. Exhaustive search approach is used to solve the optimization problem. The experiment results show k = 43 and cosine distance metric is the optimal configuration of kNN for the EEG dataset, which leads to 83.75% classification accuracy and reduces the attack success rate to 5.21%.

This study examined the effect of audit quality proxied by Auditors’ Independence (ADI), Audit Firm Size (AFS), Auditor Tenure (ADT) and Audit Firm Specialization (ADS) on shareholders’ earnings (measured as Earnings per Share - EPS) and stock performance (measured as Market Price of Stock - MPS) of listed manufacturing companies in Nigeria, in the pre-and post-International Financial Reporting Standard (IFRS) periods. To achieve this, the study used eleven (11) listed manufacturing companies listed companies that had consistently published their audited annual financial reports from 2009 to 2018. Descriptive statistics, correlation analysis and Ordinary Least Square (OLS) univariate and multiple regression technique were adopted to analyse data obtained, with the ex-post facto research design employed in the methodology. The following results were obtained from the test of hypotheses. Auditors independence, audit firm size and auditors firm specialization have significant and positive impact on EPS and MPS. However, auditors’ tenure was found to significantly affect both EPS and MPS negatively. The IFRS moderated model results revealed that audit quality variables have higher and more positive impact on EPS and MPS in the post-IFRS period, relative to the pre-IFRS, with their effects being statistically significant using the wald restriction test. The findings have direct implication on earnings management and stock performance in the Nigerian Manufacturing Industry. Keywords: Earnings Per Share, Market Price, Auditors’ Independence, Audit Firm Size, Audit Tenure, Audit Firm Specialization DOI : 10.7176/RJFA/10-24-03 Publication date: December 31 st 2019

Mandatory audit firm rotation sets a limit on the number of years a public accounting firm may audit a company’s financial statements. After a predetermined period, an accounting firm is no longer eligible to serve as the company’s auditor for a set time interval and a rotation of firms is required. The objectives of this study are: (1) to explore current audit appointment practices by audit firms in Bahrain; (2) to look into the opinions of audit firms in Bahrain on potential effects provided by implementing mandatory audit firm rotation (audit quality); and (3) to investigate audit firms’ views in implementing mandatory audit firm rotation in Bahrain. To achieve these objectives, a questionnaire was developed and distributed to respondents that consist of all auditors working in audit firms in Bahrain. The findings indicated that there is a significant relationship between mandatory audit firm rotation and quality of audit. The study also indicated that longer partner tenure makes the auditor’s performance lack the quality in the auditing process. The average mean for all questions of the hypothesis together is 2.73 with average standard deviation of 0.94 which is less than half of the mean. This means that there is no dispersion among respondents about the questions of the hypothesis. Also, the analysis shows that the t-value is 29.922, which is greater than the table critical value of t (1.66), and the p-value obtained is 0.000 which is less than the value of significance at p < 0.05. These results confirm statistically that there is a significant relationship, so the null hypothesis is rejected and the alternative hypothesis is accepted. this study focused on the impact of MAR on audit quality in Bahrain, further research may be directed towards examining the impact of MAR upon auditor independence and the cost of audit rotation. However, variables other than those included in the questionnaire of the study may affect the MAR.

Purpose: This study is motivated by the intense competition in the audit market environment which fosters audit opinion shopping practices, eventually raising critical concerns about the credibility of audit. The research examines the extent of audit opinion shopping in Nigeria, the influence of market competition on such behaviour, and the implications for audit quality. Methodology: A descriptive and correlational research design was adopted, using primary data collected from 200 auditors. Responses were analyzed using the Statistical Package for the Social Sciences (SPSS), employing descriptive statistics, reliability tests, and regression techniques. Results and conclusion: The descriptive analysis results revealed evidence of audit opinion shopping among Nigerian firms, with market competition exerting a significant influence on the likelihood of such practices. The findings also revealed that opinion shopping significantly affects audit quality, particularly in relation to timeliness, comparability, and reliability of financial statements. The study concludes that while competition may enhance efficiency in the audit market, it also provides opportunities for opportunistic opinion shopping, which undermines audit quality. Implication of findings: It recommends stronger regulatory oversight, improved enforcement of auditor independence, and the adoption of governance mechanisms that discourage frequent auditors switching for favourable opinions.

The credibility of audit quality adds value and assure investors that the investment in the company is secured. However, institutional and block-holder can affect audit quality positively or negatively. The study investigates the effect of institutional and block-holder ownership on audit quality of listed manufacturing firms in Nigeria. Logistic regression model was employed to analyze the data and test the hypotheses. Data were extracted from published audited annual reports and accounts of 32 firms that represent the sample size of the study out of the total of 59 firms. The results show that institutional ownership has negative and significant effect on audit quality while block-holder ownership has positive and significant effect on audit quality. This implies that institutional ownership reduces audit quality while block-holder ownership influences audit quality positively. The study conclude that both institutional and block-holder ownership affect audit quality and recommends that the proportion of shares acquired by institutions should be reviewed downward and that of block-holder ownership should be increased. This will encourage both institutional and block-holder ownership to put in their best to effectively monitor the quality of audit thereby give assurance and confidence to other forms of ownership in the manufacturing firms that their investments is secured.

This study examined the influence of key audit matters disclosure and auditor quality on financial reporting quality of quoted non-financial firms in Nigeria. The study adopted an ex-post facto research design. The data were gathered from a final sample size of forty-five (45) quoted nonfinancial firms representing 43% of the total population for 10 years, from 2014 to 2023. Both descriptive and inferential statistics were adopted for data analyses. The results showed that key audit matters disclosure and audit quality have a negative and statistically significant influence on discretionary accruals (a proxy for financial reporting quality), thereby improving financial reporting quality of quoted non-financial firms in Nigeria. Control variables, namely, firm size and leverage, though positive, have a non-significant influence on financial reporting quality. The findings concluded that key audit matters disclosure and audit quality are a strong pointer to critical audit issues. Its disclosure enhances transparency and improves financial reporting quality. Consequently, this study provides empirical evidence in support of key audit matters disclosure and recommended the continuity of key audit matters disclosure, as well as audit quality in enhancing financial reporting quality.

There are few tasks that managers dread as much as employee discipline. Except for cases in which the offense is severe enough to warrant termination, a manager must continue to interact daily with the employee after a punishment has been imposed. When the employee must be fired, the manager often fears that a lawsuit may not be far behind. Thus, when faced with the need to discipline an employee, supervisors might welcome help in figuring out what to do. That is the purpose of the computer expert system called the Supervisor Assistance System, created by the Florida Department of Highway Safety and Motor Vehicles (hereafter referred to as the Florida Department of Motor Vehicles). With the Supervisor Assistance System, a supervisor can first consult with the computer to determine if the employee's offense is actionable under departmental rules. If it is, the supervisor responds to a series of questions about the employee and the details of the offense. The computer then generates one or more recommendations for suggested actions to discipline the employee, along with supportive information from personnel rules. An expert system--one application of artificial intelligence--is a computerized decision-making software that structures expertise in a specific area and emulates human decision-making. The software helps users make a logical decision given its knowledge base drawn from laws, regulations, and human expertise.(1) Public agencies have used expert systems for over a decade, and they are becoming more common for a wide variety of purposes (Leonard-Barton and Sviokla, 1988; Martin, 1991). Social service departments use expert systems to determine eligibility for food stamps or refugee assistance, law enforcement units access solved and unsolved burglary cases through a computerized network to get a profile of possible perpetrators of an unsolved crime, and water testing laboratories apply for state license through an expert system. Although expert systems began as stand-alone computer programs, large public agencies are integrating their expert systems into their information data bases, and thus users may not even recognize their expert system as such (Hedberg, 1995). Most studies of public sector expert systems conclude that their promise is great, as they offer users significant potential benefits: increased productivity, improved service delivery effectiveness, and better problem anticipation (Hadden, 1989; McGowan and Lombardo, 1986; Shangraw, 1987). However, such systems have proven difficult to implement and institutionalize (Hadden, 1989, 204; Hauser and Hebert, 1992; Rubin, 1986). Few empirical studies of expert system implementation have been undertaken to assess what determines the extent to which public-sector decision makers will use an expert system initiated within their organization.(2) This article develops a model of the determinants of the degree to which managers utilize an expert system, and tests the model by examining how managers in the Florida Department of Motor Vehicles react to their expert system. The results offer lessons on how to implement an expert system in an agency so that the organization can achieve the benefits of computer technology. The Florida Department of Highway Safety and Motor Vehicles Supervisor Assistance System The Florida Department of Motor Vehicles developed the Supervisor Assistance System to provide consultations for its Supervisors on handling some 45 different employee offenses that can result in disciplinary actions.(3) (See Appendix 1 for a list of all offenses.) For any type of offense, the Supervisor Assistance System asks questions about the incident under investigation as well as other related information, such as the employee's prior disciplinary record and work history. (As an illustration, Appendix 2 presents the specific questions that the system asks a supervisor for the offense absent without authorized leave. …

With the continuous development of science and technology, exploration in the field of life sciences has become increasingly profound, encompassing the understanding of human beings themselves and the exploration of disease etiology and treatment methods.Artificial intelligence is defined as the intelligence exhibited by artificially created systems. The application of artificial intelligence is quite extensive and can replace humans in various aspects of work, significantly enhancing efficiency in daily life and work. Artificial intelligence has a dual nature, as it could provide convenience to human society but could also bring about various adverse effects.This paper summarizes the current applications of artificial intelligence in the field of life sciences. By analyzing the applications of artificial intelligence in areas such as gene editing, drug development, and bioinformatics, it demonstrates the potential of artificial intelligence in the field of life sciences. At the same time, this paper also points out the ethical, technical, social, and various challenges that the application of artificial intelligence technology in the field of life sciences faces, with the aim of providing reference for research in related fields.

There is a consistent debate in the literature on how mandatory rotation of audit firms (MAFR) contributes to audit quality (AQ). For a reason, some have adopted MAFR while others did not. This study examined MAFR to AQ based on stakeholder perceptions. Theoretical insights were established to explore on existing evidence. A descriptive survey design was carried out with a triangulation approach. Interviews were conducted while at the same time questionnaires were administered to accountants, auditors, investors, and management. A population of 71 listed and audit firms were chosen, of which 29 firms were selected using simple random, systematic and purposive sampling. Correlation and regression analysis were used to examine and interpret the quantitative data. The study's findings indicated that MAFR has a positive relationship with AQ from the linear logistic regression computed; therefore, the null hypothesis is rejected. Meanwhile, having firm audit rotation is compulsory for all listed firms, which increases competition and improves independence and new idea development which ultimately results in improved audit quality. The study, therefore, concludes that MAFR is essential. The study recommends that a further study must be done to address other factors that can enhance AQ constituting 67% shown by the ANOVA test results.

This research examines what impact the Big Data Processing Framework (BDPF) has on Artificial Intelligence (AI) applications within Corporate Marketing Communication (CMC), and thereby the research question stated is: What is the potential impact of the BDPF on AI applications within the CMC tactical and managerial functions? To fulfill the purpose of this research, a qualitative research strategy was applied, including semi-structured interviews with experts within the different fields of examination: management, AI technology and CMC. The findings were analyzed through performing a thematic analysis, where coding was conducted in two steps. AI has many useful applications within CMC, which currently mainly are of the basic form of AI, so-called rule-based systems. However, the more complicated communication systems are used in some areas. Based on these findings, the impact of the BDPF on AI applications is assessed by examining different characteristics of the processing frameworks. The BDPF initially imposes both an administrative and compliance burden on organizations within this industry, and is particularly severe when machine learning is used. These burdens foremost stem from the general restriction of processing personal data and the data erasure requirement. However, in the long term, these burdens instead contribute to a positive impact on machine learning. The timeframe until enforcement contributes to a somewhat negative impact in the short term, which is also true for the uncertainty around interpretations of the BDPF requirements. Yet, the BDPF provides flexibility in how to become compliant, which is favorable for AI applications. Finally, BDPF compliance can increase company value, and thereby incentivize investments into AI models of higher transparency. The impact of the BDPF is quite insignificant for the basic forms of AI applications, which are currently most common within CMC. However, for the more complicated applications that are used, the BDPF is found to have a more severe negative impact in the short term, while it instead has a positive impact in the long term.