Coelho, Pedro Miguel Pereira SimõesPereira, Ana Filipa Gonçalves2025-11-112025-11-112025-10-29http://hdl.handle.net/10362/190502Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and ManagementFinancial audits are one of the most powerful tools against corruption and in safeguarding transparency. Typically conducted at the end of a reference period, these audits can be extremely time-consuming and stressful for auditors. One commonly used method to perform these audits is Monetary Unit Sampling (MUS), valued for its simplicity, as it does not require detailed knowledge of the population and is available in most statistical software. However, this simplicity comes at a cost, namely larger sample sizes and greater estimated sampling errors. To address these limitations, the European Commission developed the MUS Standard Approach, which is an improved version of the traditional MUS that incorporates more information about the population, consequently mitigating some of the disadvantages of the traditional MUS. This thesis explores the Multi-Period MUS, which is a variant of the MUS Standard Approach that allows for the spreading of the audit effort throughout the reference period. The ultimate goal is to demonstrate that the Multi-Period MUS is as safe as the MUS Standard approach, and that it can be a great alias in reducing the burden and pressure on auditors. Through Monte Carlo simulations and a pseudo-population of financial transactions, the performance of each method was assessed based on the accuracy, precision, and bias of the projected error estimator. The findings suggest that, although the Multi-Period MUS exhibited greater variability in both the error and variance estimations, it delivered more accurate results. This analysis supports the conclusion that the Multi-Period MUS is a robust and effective approach for distributing the audit effort across multiple periods.engMonetary Unit SamplingMUS Standard ApproachMulti-Period MUSfinancial auditaudit burdenprojected erroraccuracyprecisionSDG 9 - Industry, innovation and infrastructureSDG 16 - Peace, justice and strong institutionsSDG 17 - Partnerships for the goalsmaster thesis204073723