Webclass 93: How can you build a successful data analytics team in internal audit?

Q1. How could you counteract the argument that data analytics is not necessary because the audit team already have total balances per third-party?

Unpaid transactions can be hidden within a creditor or debtor balance

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Totals can be better visualized in Excel

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Q2. Why might the auditors still want to use data analytics, even if they have access to SAP transaction codes?

Because the SAP transaction codes do not always give us all of the information that we need

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Because SAP transaction codes take too long to run

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Q3. Why might sampling not be sufficient for internal audit?

Because we will be unlikely to find exceptions, and even if we do, we will not be able to quantify them

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Because sampling takes too long to do

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Q4. Why might auditors want to move on from only using Excel for data analytics?

Because of the size of the data

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Because Excel is too complicated to use

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Q5. Why is it important for the “normal” auditors to be in constant contact with the data analytics team?

So that the data analytics team can be sure to do analysis that is useful to the audit and so that the auditors can be sure to be able to understand and use the results

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So that the data analytics team can understand better the data structures

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Q6. Should the “normal” auditors or the data analyst work on assessing risk based on the results of the data analytics tests?

Both should

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Only the "normal" auditors should

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Q7. When we use data we don’t need to take samples anymore

False: we still take samples to confirm our exceptions with the auditee

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True: data analytics removes the need for sampling

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Q8. If we are doing a completely new data analytics test on a new system, we should need about a week to get the data analyst to complete everything

False: it usually would take longer

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True: a week is ample time

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Q9. If we are doing standard data analytics tests on SAP then we might not need to do the technical specification and functional specification steps

TRUE

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FALSE

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Q10. In the fieldwork and the report draft it is important to get feedback/ confirmation from the auditee on the issue and recommendation

True: we should always confirm the issue to be sure that we have a good understanding of the data

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False: we don't need to confirm because data is more reliable than interviewing techniques

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Q11. What is the most critical step to complete before starting on analysing the data?

Data verification to ensure that we have the data for the correct scope and that we have understood the critical value/ date fields

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Defining the data tests that should be completed

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Webclass 93: How can you build a successful data analytics team in internal audit?

Webclass 93: How can you build a successful data analytics team in internal audit?

admin June 9, 2026

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