The role of artificial intelligence in auditing and fraud detection in accounting information systems: moderating role of natural language processing

Purpose - This study aims to investigate the moderating role of natural language processing natural language processing (NLP) on the relationship between AI-empowered AIS (data gathering, data analysis, risk assessment, detection, prevention and Investigation) and auditing and fraud detection. Design/methodology/approach - Quantitative methodology was adapted through a questionnaire. In total, 221 individuals represented the population of the study, and SPSS was used to screen primary data. The study indicated the acceptance of the hypothesis that "Artificial Intelligence in AIS has a statistically significant influence on auditing and fraud detection," showing a strong correlation between auditing and fraud detection. The study concluded that NLP moderates the relationship between AI in AIS and auditing and fraud detection. Findings - The study's implications lie in its contribution to the development of theoretical models that explore the complementary attributes of AI and NLP in detecting financial fraud. Research limitations/implications - A cross-sectional design is a limitation. Practical implications - NLP is a useful tool for developing more efficient methods for detecting fraudulent activities and audit risks. Originality/value - The study's originality stems from its focus on the use of AI-empowered AIS, a relatively new technology that has the potential to significantly impact auditing and fraud detection processes within the accounting field.