Audit Evidence Collection Techniques AAIA Practice Questions (Page 2)

Questions 6–10

1. 6application · medium

   An auditor is planning evidence collection for an AI-based credit scoring system. The system uses customer data from multiple source systems, including a CRM, a transaction database, and an external credit bureau feed. The audit objective is to verify that the model's decisions comply with fair lending regulations. Which of the following is the most appropriate first step in the evidence collection plan?

   • AInterview the model developers to understand the algorithm and then decide which data sources to include.
   • BDefine the audit scope and objectives, and identify the relevant data sources and stakeholders for the AI system.
   • CImmediately extract all data from the CRM, transaction database, and credit bureau feed to avoid missing any potential evidence.
   • DRequest a copy of the model's training data from the data science team to ensure the audit covers the model's development.
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2. 7application · medium

   An auditor has completed evidence collection for an AI system audit. The evidence includes logs, interview notes, and extracted data. The audit is subject to a regulatory requirement that evidence be retained for five years. Which of the following is the most appropriate action for the auditor to take?

   • ADelete the evidence after the audit report is issued to reduce storage costs.
   • BKeep the evidence on the auditor's personal laptop for easy access.
   • CProvide the evidence to the system's vendor for safekeeping.
   • DStore the evidence in a secure, access-controlled repository with a documented retention schedule that meets the five-year requirement.
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4. 8foundation · easy

   Which of the following is a manual evidence collection technique?

   • AConducting interviews with system users.
   • BDeploying a monitoring agent to capture runtime metrics.
   • CUsing a log parser to aggregate system logs.
   • DRunning a SQL query to extract transaction data.
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5. 9foundation · easy

   During data transformation for an AI audit, why is it important to document the transformation steps?

   • ATo ensure that the transformation process is reproducible and transparent.
   • BTo reduce the need for data validation.
   • CTo eliminate the need for audit evidence retention.
   • DTo speed up the data extraction process.
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6. 10expert · hard

   An auditor is collecting evidence from an AI system that processes real-time transactions. The system generates a large volume of logs, and the auditor needs to collect evidence for a specific time period. The auditor is concerned about the performance impact of the collection on the production system. Which of the following is the most appropriate approach?

   • AManually copy the logs from the system's console during peak hours.
   • BRun a continuous real-time stream of logs to the auditor's machine.
   • CRequest a full database backup from the system administrator.
   • DUse an automated script that queries the logs in batches during off-peak hours to minimize impact.
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