Sampling and Audit Analytics

for Internal Auditors

Audit Analytics

Modern Internal Audit increasingly relies on data-driven techniques to identify anomalies, operational patterns and potential risk indicators. Audit Analytics helps auditors focus their effort on the areas of highest relevance.

Statistical Sampling

Statistical sampling techniques help auditors define sample sizes, measure sampling risk and project results to the whole population using mathematically structured approaches.

Data Analysis

Data Analysis techniques such as regression analysis, Benford’s Law and trend analysis help auditors detect unusual behaviour, operational deviations and potential red flags within large datasets.

Audit Analytics Tools Available in this Platform

This website has been specifically designed for Internal Auditors and makes available the following tools.

• Regression Analysis

Identify operational outliers, unusual relationships and red flags through statistical modelling and prediction bands.
The platform helps auditors interpret analytical results through guided assessments and automated working papers.

• Statistical Sampling

Apply structured statistical sampling techniques to estimate error rates, measure sampling risk and project audit results to the entire population.
The platform supports multiple audit-oriented sampling methodologies and automated sample selection procedures.

• Monetary Unit Sampling

Perform Monetary Unit Sampling (MUS) on financial populations to evaluate the accuracy of account balances and monetary values through statistically driven sample selection and projection techniques.

• Trend Analysis
  

Identify unusual spikes, drops or behavioural variations over time through automated trend analysis techniques designed to support operational and financial reviews.

• Benford’s Law
  

Identify irregular digit distributions that may indicate anomalies, processing errors or potential fraud patterns within large numerical datasets.