TIAPS ALB_Module 2E. Data Analytics for Internal Auditing

This can help managers identify and react to problems or opportunities. Some causes of
variances are purely random and can be eliminated. The comparison of two sets of data can
help determine the extent to which they are correlated.
Variance analysis is discussed further in Module 3.
2E.2.2 Trend Analysis
Trends are changes (or variances) in data over time. The changes observed may be:
• Random, to be identified and eliminated or ignored.
• Cyclical, recurring over short cycles, such as higher demands for customer services
at certain times of the day or week.
• Seasonal, recurring over longer cycles, such as peaks and troughs in sales of ice
cream over a year.
• Underlying trends, being the true long-term pattern, often over multiple years, having
isolated random, cyclical, and seasonal factors. Often underlying trends are most
apparent when we can compare data from the some point in a cycle, season, or year
over multiple cycles, seasons, or years.
2E.2.3 Reasonableness Testing
Reasonableness testing is another form of variance or trend analysis in which reported or
apparent performance is compared with what might reasonably have been expected, once
the forecast is adjusted to take account of everything that is known. Variances may highlight
errors or deliberate misstatements. When there seems to be no reasonable explanation,
when things look too good or too bad to be true, then it deserves further investigation.
2E.2.4 Ratio Estimation
Findings based on a sample of data can be extrapolated to make assumptions about the
remaining data or used as the basis for forecasting. Larger samples help reduce the
likelihood of bias but there is no guarantee the sample is representative of the whole
population. Statistical modeling is used to calculate the degree of confidence in the analysis.
2E.2.5 Benchmarking
Comparing actual performance with benchmarking data can help identify errors,
weaknesses, and opportunities for improvement to align more closely with best practice.
2E.2: Reflection
Consider these commonly used methods for analysis of data:
Variance analysis
Trend analysis
Reasonable testing
Ratio estimation
Benchmarking
Which of these do you commonly use?
Which of these do you feel you need more help in developing your competency?
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