AI in Financial Auditing Quiz

Answers and explanations appear as you take the quiz.

1. What does traditional audit sampling involve?
   • Testing every transaction by hand
   • Letting management choose which transactions to test
   • Testing a chosen subset of transactions and extrapolating to the whole
   • Only reviewing the largest transaction each year
2. According to the guide, what does full-population testing actually mean?
   • Every entry is screened, and the flagged exceptions still need investigation
   • Every entry has been fully verified with evidence
   • The auditor no longer needs to exercise judgment
   • Only entries above a materiality threshold are examined
3. Which standards require auditors to test journal entries for management override of controls?
   • ISA 530 and AS 2315
   • ISA 240 and PCAOB AS 2401
   • Only internal company policies
   • Tax filing regulations
4. Which of these is a classic journal entry red flag?
   • An automated entry posted by the billing system at the usual time
   • A payroll entry matching the approved headcount
   • A depreciation entry calculated by the fixed-asset system
   • A manual entry for an amount just below an approval limit
5. Why are unsupervised models such as isolation forests useful for journal entry analysis?
   • They guarantee every fraud is found
   • They replace the need for a trial balance
   • They score how rare an entry is without needing labeled fraud examples, which are scarce
   • They only work on round-number entries
6. What should an auditor do before running analytics on an extracted ledger?
   • Reconcile the extracted entries to the trial balance to confirm completeness and accuracy
   • Delete duplicate rows without investigation
   • Tune thresholds until few exceptions appear
   • Ask the model to certify the data
7. How does the guide characterize Benford's law analysis?
   • Conclusive proof of manipulation
   • A way to highlight populations worth a closer look, not proof
   • A replacement for journal entry testing
   • A method banned by auditing standards
8. Which behavior reflects professional skepticism when using AI audit tools?
   • Accepting a clean dashboard as proof there are no issues
   • Dismissing large exception lists in bulk
   • Letting the tool decide materiality
   • Evaluating data reliability and guarding against over-trusting a model's clean result