Artificial Intelligence and Machine Learning in Accounting and Finance: Theories and Applications

Dear Colleagues,

In recent years, we have witnessed a paradigm shift in various sectors, engendered by the profound transformation induced by artificial intelligence (AI) and machine learning (ML). These rapidly evolving fields have inscribed a new narrative across a multitude of industries, carving out novel frontiers in the process. Among the disciplines touched by this technological revolution, accounting and finance stand out as pivotal beneficiaries. AI and ML, with their robust computational capabilities, have been progressively integrated into a range of applications within the realms of accounting and finance. Their potential has been harnessed to revolutionize financial modeling, transforming it from a traditional statistical exercise into a dynamic and adaptable mechanism. Furthermore, risk management has been enhanced significantly, evolving from relying on historical data to predictive systems capable of anticipating and responding to possible future scenarios. In the auditing domain, AI and ML have introduced automation and advanced data analytics, thus enabling more comprehensive, accurate, and efficient audit processes. Moreover, these technologies are becoming instrumental in ensuring regulatory compliance, as they are capable of continuously monitoring and assessing vast amounts of data against ever-changing regulatory requirements. Their contribution extends beyond improving efficiency and accuracy; they provide unprecedented insights that are transforming decision-making processes. With this backdrop, we strongly encourage researchers to submit their scholarly work that illuminates the varied applications and impacts of AI and ML within the domain of accounting and finance. The aim is to foster a nuanced understanding of how these advanced technologies are reshaping the landscape of these fields, and the broader implications for organizations, industry professionals, and policymakers. Potential topics include, but are not limited to:

• Application of AI and ML in financial decision-making
• ML based portfolio optimization for risk management
• Financial fraud detection based on big data analytics
• Predictive models in finance and accounting using AI and ML
• Role of AI and ML in risk management and auditing
• Integration of AI and ML with blockchain technologies in accounting and finance
• AI and ML in financial services and fintech
• Ethical, social, and regulatory implications of AI and ML in accounting and finance
• Case studies showcasing successful applications of AI and ML in the accounting and finance sector

Authors are expected to contribute to the body of knowledge in the field by presenting novel theoretical perspectives, innovative methodologies, or empirical findings. Submissions that offer insights into the practical implications for industry professionals and policymakers are also highly desirable.

Prof. Dr. Xinwei Cao
Dr. Tran Thu Ha
Prof. Dr. Dunhui Xiao
Dr. Vasilios N. Katsikis
Dr. Ameer Hamza Khan
Prof. Dr. Shuai Li
Topic Editors