<![CDATA[This study examines how data analytics enhances risk assessment procedures in audits, The research used case study as method, the data collected at Guangzhou Yican Trading Co. Traditional auditing methods often rely on manual sampling, which increases the risk of undetected anomalies. With the growing complexity of financial data, integrating analytics can improve fraud detection and risk mitigation. A qualitative approach was used, incorporating semi-structured interviews and case study analysis. Findings indicate that data analytics allows for full dataset analysis, real-time risk monitoring, and enhanced fraud detection. However, challenges such as limited technical expertise, resistance to change, and integration issues with legacy systems hinder full adoption. To overcome these challenges, this study recommends structured training programs, investment in analytics tools, and the development of a standardized framework for data-driven auditing. The research contributes to management accounting and auditing by demonstrating how analytics transforms modern risk assessment methodologies.]]>
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