Thesis Abstract

Abstract
The integration of artificial intelligence (AI) technologies in accounting practices has been gaining significant momentum in recent years, with a particular focus on its impact on financial statement analysis. This thesis aims to investigate the implications of AI on financial statement analysis within the accounting domain, exploring how these technologies are transforming traditional practices and decision-making processes. The study adopts a mixed-methods approach, combining qualitative and quantitative analyses to provide a comprehensive understanding of the subject matter. The thesis begins with an introduction that sets the context for the research, followed by a detailed background study that examines the evolution of AI in accounting and its relevance to financial statement analysis. The problem statement identifies the gaps in existing literature and highlights the need for further exploration in this area. The objectives of the study are outlined to guide the research process, focusing on assessing the effectiveness of AI tools in enhancing financial statement analysis accuracy and efficiency. Limitations of the study are acknowledged, recognizing the constraints that may impact the research findings. The scope of the study is defined to delineate the boundaries within which the research will be conducted, outlining the specific aspects of financial statement analysis that will be investigated. The significance of the study is discussed, emphasizing the potential contributions to the accounting profession and the broader implications for decision-making processes in organizations. The structure of the thesis is outlined to provide a roadmap for the subsequent chapters, detailing the organization of content and the flow of information. Definitions of key terms are provided to clarify the terminology used throughout the thesis. Chapter Two presents a comprehensive literature review that synthesizes existing research on AI in accounting and financial statement analysis. Ten key themes are identified and analyzed to provide a theoretical foundation for the study, exploring the current state of knowledge in this field. Chapter Three focuses on the research methodology, outlining the research design, data collection methods, sampling techniques, and data analysis procedures. The chapter also discusses the ethical considerations involved in the research process and justifies the chosen methodology for the study. Chapter Four presents the findings of the research, detailing the outcomes of the data analysis and discussing the implications of the results. The chapter examines the impact of AI technologies on financial statement analysis and evaluates the effectiveness of these tools in enhancing decision-making processes. Chapter Five concludes the thesis by summarizing the key findings, discussing their implications for accounting practice, and highlighting areas for future research. The study contributes to the growing body of knowledge on the intersection of AI and financial statement analysis, offering valuable insights for practitioners and researchers in the field of accounting.

Thesis Overview