Artificial intelligence and its applications in financial process and finance: A bibliometric analysis

Abstract

Artificial intelligence (AI) is increasingly utilized in different industries, particularly financial services, where it handles functions traditionally performed by humans, yet a significant gap exists in understanding its real-world applications in corporate reporting. This research purposes to contribute to the financial process and finance literature by reviewing comprehensively how previous literature have addressed the topic of Artificial Intelligence and its Applications in financial process and Finance. This study aims to address these gaps through conducting a bibliometric analysis, focusing on peer-reviewed articles from 2010 to 2024. The study's findings highlighted a marked increase in research output, particularly during the COVID-19 pandemic, highlighting the integration of AI in financial and financial process research by enhancing accuracy and reducing errors in financial reporting. The analysis highlighted a collaborative effort among researchers, primarily from China and the United States, for the advancements in this field. AI dominates financial process and finance research, with key terms like machine learning, blockchain, big data, and deep learning highlighting a multidisciplinary approach to enhance efficiency and decision-making. However, challenges such as data protection and ethical considerations remain prevalent. The findings and discussions emphasized the need for new regulatory frameworks and skill development for professionals to adapt to these technological changes. Future research should explore the implications of AI on corporate governance and accountability, providing a way for innovative practices in the industry. This study contributed valuable insights into AI's transformative potential, providing practitioners and policymakers with knowledge to navigate the evolving landscape of finance and Financial Process.