A systematic literature review of the role of big data analysis in financial auditing/ Iyad Hosni Mohammed Ismail and Fathilatul Zakimi Abdul Hamid

Big data analysis is increasingly important in financial auditing, yet its application in audit engagements lags behind. Despite the belief that data analysis will shape auditing in the future, limited publications have explored this transformative potential. This study investigated the role of big data analysis in auditing, and the opportunity to depict the development of this study trend and predict its future growth prospects in future audit assignments. Opportunities for and challenges of future auditing research have also been covered. The use of data analytics in auditing has a great deal of promise to improve audit quality, reduce errors, increase process transparency, and boost stakeholders' credibility. Researchers grounded upon the systematic literature review (SLR) using the PRISMA approach of 97 scientific articles extracted from Scopus and other scientific databases between the years 1990 and 2023. Analysis outcomes revealed the importance of IT knowledge, data categorization, and diverse skills for effective utilization. Challenges include data volume, lack of standards, and negative perceptions. Integration of advanced technologies like robots, AI, and blockchain showed promise for revolutionizing auditing and enhancing cybersecurity. Data specialists and digital tools improve efficiency and decision-making. Factors influencing the adoption and implementation of big data analysis in audits were identified. Implications, limitations, and future research directions are discussed for further investigation into enhancing audit processes and decision-making in the digital age.