Artificial intelligence applications in auditing processes in the banking sector

Abstract

This research provides an in-depth examination of the role artificial intelligence (AI) plays in revolutionizing bank auditing and quality control processes. By integrating AI technologies, the banking industry stands on the edge of a transformative era where the efficiency, accuracy, and security of auditing operations are significantly enhanced. This systematic mapping study (SMS) explores the extent of AI’s adoption in bank audits, specific areas of its application, its impact on auditing processes, challenges, and the dynamics of human-AI collaboration in auditing. The findings reveal AI’s pivotal roles in enhancing credit risk analysis, operational efficiency, fraud detection, cybersecurity, and bankruptcy prediction, through analyzing complex data, identifying patterns, and ensuring financial stability, which leads to streamlining operations, detecting fraudulent activities through advanced pattern recognition, boosting cybersecurity measures, and accurately forecasting bankruptcy risks, thereby offering a robust tool for risk management and decision-making in the banking sector. By filling a critical gap in the literature, the study advances our understanding of AI’s capabilities, limitations, ethical considerations of AI integration, and the need for further research to overcome technological challenges and ethical dilemmas. The comprehensive analysis offers valuable insights for academic debate, businesses, and regulators to enhance the quality, efficiency, and security of financial auditing practices in the digital age.