This study examines financial auditing’s role in fraud detection and accounting integrity. It explores methodologies to identify irregularities and mitigate corporate fraud risks. Key audit tests, including Monetary Unit Sampling (MUS)—prioritizing high-value items—and Random Sampling, are analyzed, detailing their applications, strengths, and limitations. The paper also investigates Audit Analysis techniques for systematic data evaluation, risk assessment, and internal control review, which are crucial for detecting anomalies and enhancing financial reliability. Findings indicate that integrating statistical methods with qualitative analysis improves audit effectiveness, fostering transparency and compliance. The study underscores adaptive strategies to address corporate complexities, advocating combining random and Monetary Unit Method to strengthen fraud prevention and accountability. This research contributes to auditing literature, promoting precision and trustworthiness in dynamic business environments.

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Auditing,Monetary unit method