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  4. Data analytics for quality reporting and effective auditing = 數據分析對會計報告品質與審計有效性之影響
 
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Data analytics for quality reporting and effective auditing = 數據分析對會計報告品質與審計有效性之影響

Principal Investigator
Dr. LEE Hua  
Investigator
Dr. CHEN Wan Yu, Tina  
Dr. XIE Yuying, Sabrina  
Department
Department of Accounting  
Grant Awarding Body
Research Grants Council
Grant Type
Inter-Institutional Development Scheme (IIDS)
Project Code
UGC/IIDS15/B01/20
Amount Awarded
HK$572,340
Funding Year
2020-2021
Duration of the Project
12 months
Status
Completed
Abstract
Data analytics has been one of the most significant fields in the ever-changing business world. The rapid advancement of information technology and electronic devices promotes data accumulation in the changed business models, strategies, and operations, and enhances the value of business information in today’s data-driven business environment. Facing this revolution, the audit profession has developed new techniques and standards in the auditing of financial statements and fraud detection. This project explores the impact of data science on the quality of accounting information and the effectiveness of financial statement audits and fraud detection. Major issues include how data analytics can improve the usefulness of accounting information for investment and management decision-making, how data analytics enhance audit procedures and audit evidence examination for financial statement audits, and how data analytics can help auditors to detect and predict fraud and assess the risk of fraud. The results will provide practical implications and contribute to both accounting education and research as well as regulatory authorities.
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