Thesis Abstract

Abstract
The integration of artificial intelligence (AI) technologies into the field of accounting has significantly transformed traditional financial statement analysis processes. This study aims to investigate the impact of AI on financial statement analysis in accounting and its implications for financial decision-making. The research methodology involves a comprehensive literature review, data collection, and analysis of findings from both theoretical and practical perspectives. Chapter One provides an introduction to the research topic, including the background of the study, problem statement, objectives, limitations, scope, significance, and structure of the thesis. Chapter Two presents a detailed literature review, exploring ten key areas related to AI applications in financial statement analysis and accounting practices. The literature review covers topics such as machine learning algorithms, data analytics, audit automation, fraud detection, risk assessment, and regulatory compliance. Chapter Three outlines the research methodology employed, including the research design, data collection methods, sampling techniques, data analysis procedures, and validation strategies. This chapter also discusses the ethical considerations and limitations of the research process. Chapter Four presents a thorough discussion of the research findings, analyzing the impact of AI technologies on financial statement analysis and evaluating the benefits and challenges associated with their implementation in accounting practices. The study highlights the potential of AI to enhance the accuracy, efficiency, and reliability of financial statement analysis, leading to improved decision-making processes for stakeholders. However, the research also identifies limitations and risks, such as data privacy concerns, algorithm bias, and the need for human oversight in AI-driven analyses. The implications of these findings are discussed in the context of regulatory frameworks, professional standards, and ethical considerations in accounting practices. In conclusion, Chapter Five summarizes the key findings of the study, highlighting the transformative potential of AI technologies in financial statement analysis and accounting. The research contributes to the existing body of knowledge by providing insights into the practical applications of AI in enhancing financial analysis processes and shaping the future of accounting practices. Recommendations for future research and practical implications for accounting professionals and organizations are also discussed. Overall, this thesis offers valuable insights into the evolving role of AI in financial statement analysis and underscores the importance of adapting accounting practices to leverage the benefits of technological advancements in the digital era.

Thesis Overview