CONSEQUENCES OF BIG DATA AND FORMALIZATION ON ACCOUNTING AND AUDITING STANDARDS

CONSEQUENCES OF BIG DATA AND FORMALIZATION ON ACCOUNTING AND AUDITING STANDARDS IN NIGERIA

ABSTRACT

This research abstract examines the effects of formalization and big data integration on Nigerian accounting and auditing standards. Big data’s emergence and growing significance across a number of industries have made it necessary to include it into accounting and auditing procedures. This study intends to investigate the effects on the Nigerian financial sector of the formalization of accounting and auditing standards and the use of big data.

The study will use a mixed-methods approach that combines quantitative data analysis with qualitative interviews with important stakeholders, including experts from the accounting and auditing sectors, regulatory organizations, and pertinent governmental authorities. To get thorough understanding of the subject, the study will examine both primary and secondary sources of information.

The integration of big data into Nigerian accounting and auditing standards is expected to have a variety of effects. First off, big data analytics deployment can improve the effectiveness and efficiency of financial reporting operations. It may make real-time data analysis easier, allowing auditors to spot abnormalities, patterns, and trends more quickly and correctly. This can raise openness and accountability, eliminate errors, and generally improve the quality of financial reporting. Second, a uniform and trustworthy financial reporting system in Nigeria can be created by formalizing accounting and auditing standards through the adoption of standardized frameworks and principles. Nigerian accounting and auditing procedures can be brought into line with international best practices by implementing widely accepted standards like the International Financial Reporting Standards (IFRS) and International Standards on Auditing (ISA). This alignment might increase investor confidence, draw in foreign capital, and foster economic expansion.

However, the integration of big data and formalization also poses challenges and potential risks. Ensuring data privacy, security, and protection against unauthorized access and manipulation is crucial. Moreover, the Nigerian financial sector needs to address the digital divide and ensure adequate infrastructure, technical expertise, and training to effectively implement big data analytics and standardized accounting and auditing practices across the country.

Policymakers, regulators, professional accounting and auditing bodies, and practitioners will benefit from knowing the potential advantages, difficulties, and necessary steps to successfully implement and leverage big data analytics and formalized standards in the Nigerian context from the research’s findings, which will contribute to the literature on the effects of big data and formalization on accounting and auditing standards, specifically in the Nigerian context. It provides an overview of the topic, research methodology, expected consequences, and potential challenges. For a complete research paper, additional sections such as introduction, literature review, methodology, results, discussion, and conclusion would be required.

 

Table of Contents
Title Page – – – – – – – – – – i
Declaration – – – – – – – – – – ii
Certification – – – – – – – – – – iii
Dedication – – – – – – – – – – iv
Acknowledgements – – – – – – – – – v
Table of Contents – – – – – – – – – vi
List of Tables – – – – – – – – – – x
List of Appendices – – – – – – – – – – xi
Abstract – – – – – – – – – – xii

 

CHAPTER ONE

INTRODUCTION

1.1 Background to the Study – – – – – – – – 1
1.2 Statement of the Problem- – – – – – – – 3
1.3 Research Questions- – – – – – – – – 5
1.4 Objectives of the Study- – – – – – – – – 6
1.5 Research Hypotheses- – – – – – – – – 6
1.6 Scope of the Study- – – – – – – – – 7
1.7 Significance of the Study- – – – – – – – 7

1.8 Limitations of the Study- – – – – – – – 8

CHAPTER TWO
LITERATURE REVIEW AND THEORETICAL FRAMEWORK
2.1 Introduction- – – – – – – – – – 9
2.2 General review
2.3 Review of related article
2.4 Review of Empirical Studies – 13
2.5 Theoretical Framework- – – – – – – – 18
2.6.1 Expectation Disconfirmation Theory- – – – – – – 19

 

CHAPTER THREE
METHODOLOGY
3.1 Introduction- – – – – – – – – – 23
3.2 Research Design- – – – – – – – – 23
3.3 Population of the Study- – – – – – – – – 23
3.4 Sample Size and Sampling Technique- – – – – – – 23
3.5 Source and Methods of Data Collection- – – – – – 25
3.6 Measurement of Variables- – – – – – – – 26
3.7 Techniques of Data Analysis- – – – – – – – 26
3.8 Justification for Technique of Data Analysis- – – – – – 26
3.9 Research Model- – – – – – – – – – 27

CHAPTER FOUR
DATA PRESENTATION AND ANALYSIS
4.1 Introduction- – – – – – – – – – 28
4.2 Response Rate – – – – – – – – – 28
4.3 Data Screening and Preparation- – – – – – – 29
4.3.1 Analysis of Missing Values- – – – – – – – 29
4.3.2 Analysis of Outliers – – – – – – – – – 30
4.4 Results of Reliability and Validity Assessment- – – – – 30

CHAPTER FIVE
SUMMARY, CONCLUSION AND RECOMMENDATIONS
5.1 Summary of Findings – – – – – – – – 40
5.2 Conclusion – – – – – – – – – 41
5.3 Recommendations – – – – – – – – 41
5.4 Suggestions for Future Studies – – – – – – – 42
References – – – – – – – – – – 44

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