Noorhayati, Mansor and Nor Raihana Asmar, Mohd Noor (2019) Exploring the Adaptation of Artificial Intelligence in Whistleblowing Practice of the Internal Auditors in Malaysia. In: 16th International Learning and Technology Conference, L and T 2019;, 30-31 January 2019, Effat UniversityJeddah; Saudi Arabia.
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Abstract
News of high-profile frauds and financial malpractices continue to make daily media headlines after the change of government in May 2018. Whether in the private or government sector, corruptions, financial misconduct and malpractices have always been associated with lack of proper auditing and ineffective internal control systems. Various initiatives have been developed to reduce the negative perception of public sector frauds including the implementation of whistleblowing practices in public sector. However, to date, it is still questionable whether this practice is efficient and effective due to the increasing trend in reported frauds in the government departments. Thus, this study examines the practice of whistleblowing in Malaysian public sector agencies. Total of 500 questionnaires are distributed to the internal auditors in public sector agencies. To achieve the objective of this study, the application of artificial intelligence in the practice of the whistleblowing will be examined to see the effectiveness of this practice. The findings are expected to enhance the new Malaysian government initiatives in fighting frauds and corruptions. The effect of whistleblowing practice will provide further evidence to strengthen the internal control system and practices and improve the public sector accountability and transparency
Item Type: | Conference or Workshop Item (Paper) |
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Uncontrolled Keywords: | Financial misconduct, Government departments, Government sectors, Malaysian governments, Malaysian public sectors, Public sector agencies, Public services, whistleblowing |
Subjects: | H Social Sciences > HG Finance |
Divisions: | Faculty of Business and Management |
Depositing User: | Muhammad Akmal Azhar |
Date Deposited: | 23 Nov 2020 08:21 |
Last Modified: | 23 Nov 2020 08:21 |
URI: | http://eprints.unisza.edu.my/id/eprint/1871 |
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