ARTIFICIAL INTELLIGENCE (AI) AND FINANCIAL REPORTING INTEGRITY IN MALAYSIA: A CONCEPTUAL REVIEW OF CHALLENGES AND IMPLICATIONS IN EXTERNAL AUDITING

Abstract

The integrity of financial reporting is important for maintaining stakeholder trust and the efficient functioning of capital markets. Independent auditors are entrusted with the responsibility of providing reasonable assurance that financial statements are free from material misstatement, whether caused by error or fraud. Despite established auditing standards and frameworks, financial statement fraud persists globally, as such the recent scandals, Khazanah FashionValet Investment Controversy in 2024 and 1Malaysia Development Berhad (1MDB) scandals that are involving of several countries, raising concerns about the responsibility of auditors in detecting and preventing such malpractices. Moreover, the increasing complexity of financial transactions, combined with the growing reliance on digital technology, has increased the need for effective external auditing processes and external auditor positions to assure the integrity of financial reports. Thus, Artificial Intelligence (AI) has emerged as an invaluable instrument in auditing, including skills such as data analytics, detection of anomalies, and predictive modelling to assist auditors in detecting errors or fraud in financial misstatements. AI assist auditor in planning the appropriate auditing techniques and will help them to enhance their audit quality, efficiency and risk assessment. However, despite the growing adoption of AI in auditing, there is a quite challenging to the independent auditors especially in developing country like Malaysia. Therefore, this study will explore the challenges and implications about the auditors’ adoption of AI to the financial reporting integrity by reviewing previous literatures and relevant sources such as academic articles, technical report or announcements from regulatory bodies and news. By examining the impacts of the auditors’ AI adoption towards financial reporting integrity, this conceptual paper aims to provide the ideas to audit firms, regulators, and standard-setting bodies on the best practices for integrating AI into auditing frameworks. Additionally, this study contributes to the discourse on whether the auditor’s adoption of AI can uphold, enhance, or potentially undermine financial reporting integrity.