Isaca AAIA Practice Test 113
Question 1120
An independent AI auditor reviews this case: An auditor flags every spike in model-denial rate as misconduct without adjusting for changing application volumes. Which TWO complementary elements should the auditor seek: an effective corrective control and the most probative independent evidence? Select TWO answers.
- Convert any unusual dashboard trend directly into a confirmed AI control failure finding.
- Inspect seasonality, cohort mix, outliers, confidence intervals, drift metrics and independent transactions.
- Define the AI audit universe and scope using use-case impact, third parties, control reliance and key risk scenarios.
- Review challenge samples, model changes, error rates, reviewer overrides and data privacy restrictions.
- Use context-aware segment and time analysis with corroboration, uncertainty and appropriate baseline comparisons.
Explanation
Correct Answers
B:The reason it is necessary is: An anomaly is a hypothesis requiring data quality and causal investigation, not automatic proof of a control failure. For this situation: An auditor flags every spike in model-denial rate as misconduct without adjusting for changing application volumes.
E:This response fits the risk associated with Audit analytics drift and anomalous trend interpretation: Use context-aware segment and time analysis with corroboration, uncertainty and appropriate baseline comparisons.
Incorrect Answers
A:This attractive shortcut does not resolve the Audit analytics drift and anomalous trend interpretation weakness: Convert any unusual dashboard trend directly into a confirmed AI control failure finding. Effective closure requires: Audit analytics identify defensible exceptions while avoiding unsupported causal and discriminatory conclusions.
C:This option concerns Risk-based AI audit universe and scope, which is a related but different AI governance concern. For this situation: An auditor flags every spike in model-denial rate as misconduct without adjusting for changing application volumes.
D:This option concerns Validation of AI-enabled audit analytics tools, which is a related but different AI governance concern. It does not establish control effectiveness for Audit analytics drift and anomalous trend interpretation.
Question 1121
A governance and assurance review uncovers the following: A credit AI's subgroup error rises gradually but standard dashboards only show one combined monthly average. What is the MOST appropriate risk-based audit recommendation that addresses the root control weakness? Select ONE best answer.
- Convert any unusual dashboard trend directly into a confirmed AI control failure finding.
- Document reproducible extraction, definitions, feature joins, calculations and review of exceptions.
- Use context-aware segment and time analysis with corroboration, uncertainty and appropriate baseline comparisons.
- Reconcile source populations, failed records, joins and transformations before interpreting AI audit analytics.
Explanation
Correct Answer
C:The reason it is necessary is: An anomaly is a hypothesis requiring data quality and causal investigation, not automatic proof of a control failure. In this case: A credit AI's subgroup error rises gradually but standard dashboards only show one combined monthly average.
Incorrect Answers
A:This attractive shortcut does not resolve the Audit analytics drift and anomalous trend interpretation weakness: Convert any unusual dashboard trend directly into a confirmed AI control failure finding. In this case: A credit AI's subgroup error rises gradually but standard dashboards only show one combined monthly average.
B:This option concerns Reproducible audit data transformations, which is a related but different AI governance concern. The decisive principle here is: An anomaly is a hypothesis requiring data quality and causal investigation, not automatic proof of a control failure.
D:This option concerns Audit data completeness and reconciliation, which is a related but different AI governance concern. It does not establish control effectiveness for Audit analytics drift and anomalous trend interpretation.
Question 1122
A risk-based audit engagement examines this operating condition: A credit AI's subgroup error rises gradually but standard dashboards only show one combined monthly average. Which principle BEST explains why the observed practice is a material governance or control concern? Select ONE best answer.
- AI-assisted audit planning can improve coverage but retains risks of confidentiality, bias and fabricated conclusions.
- An anomaly is a hypothesis requiring data quality and causal investigation, not automatic proof of a control failure.
- Convert any unusual dashboard trend directly into a confirmed AI control failure finding.
- Incomplete populations and silent joins can bias control effectiveness conclusions.
Explanation
Correct Answer
B:The acceptable verified outcome is: Audit analytics identify defensible exceptions while avoiding unsupported causal and discriminatory conclusions. In this case: A credit AI's subgroup error rises gradually but standard dashboards only show one combined monthly average.
Incorrect Answers
A:This option concerns Using AI during audit engagement planning, which is a related but different AI governance concern. The decisive principle here is: An anomaly is a hypothesis requiring data quality and causal investigation, not automatic proof of a control failure.
C:This attractive shortcut does not resolve the Audit analytics drift and anomalous trend interpretation weakness: Convert any unusual dashboard trend directly into a confirmed AI control failure finding. For this situation: A credit AI's subgroup error rises gradually but standard dashboards only show one combined monthly average.
D:This option concerns Audit data completeness and reconciliation, which is a related but different AI governance concern. For this situation: A credit AI's subgroup error rises gradually but standard dashboards only show one combined monthly average.
Question 1123
An audit committee asks for a defensible assessment of this situation: A credit AI's subgroup error rises gradually but standard dashboards only show one combined monthly average. What evidence should the auditor examine FIRST to substantiate or challenge the control owner’s claim? Select ONE best answer.
- Inspect source test inputs, environment version, expected result, output logs and exception handling.
- Inspect seasonality, cohort mix, outliers, confidence intervals, drift metrics and independent transactions.
- Convert any unusual dashboard trend directly into a confirmed AI control failure finding.
- Inspect approved tool use, input sensitivity, model version, generated risk ranking and reviewer corrections.
Explanation
Correct Answer
B:The reason it is necessary is: An anomaly is a hypothesis requiring data quality and causal investigation, not automatic proof of a control failure. This evidence directly tests the asserted control for Audit analytics drift and anomalous trend interpretation: Inspect seasonality, cohort mix, outliers, confidence intervals, drift metrics and independent transactions.
Incorrect Answers
A:This option concerns Reperformance and adversarial audit test cases, which is a related but different AI governance concern. The decisive principle here is: An anomaly is a hypothesis requiring data quality and causal investigation, not automatic proof of a control failure.
C:This attractive shortcut does not resolve the Audit analytics drift and anomalous trend interpretation weakness: Convert any unusual dashboard trend directly into a confirmed AI control failure finding. Use context-aware segment and time analysis with corroboration, uncertainty and appropriate baseline comparisons.
D:This option concerns Using AI during audit engagement planning, which is a related but different AI governance concern. For this situation: A credit AI's subgroup error rises gradually but standard dashboards only show one combined monthly average.
Question 1124
During an AI controls assessment, the team learns that a credit AI's subgroup error rises gradually but standard dashboards only show one combined monthly average. After management addresses the issue, which result MOST convincingly demonstrates effective remediation? Select ONE best answer.
- The plan covers material high-risk deployments and states documented scope boundaries and assurance limitations.
- Independent repeat tests reproduce control behavior and deviations generate substantiated findings.
- Audit analytics identify defensible exceptions while avoiding unsupported causal and discriminatory conclusions.
- Convert any unusual dashboard trend directly into a confirmed AI control failure finding.
Explanation
Correct Answer
C:The reason it is necessary is: An anomaly is a hypothesis requiring data quality and causal investigation, not automatic proof of a control failure. This is an observable validation result for Audit analytics drift and anomalous trend interpretation, not just management assurance: Audit analytics identify defensible exceptions while avoiding unsupported causal and discriminatory conclusions.
Incorrect Answers
A:This option concerns Risk-based AI audit universe and scope, which is a related but different AI governance concern. The decisive principle here is: An anomaly is a hypothesis requiring data quality and causal investigation, not automatic proof of a control failure.
B:This option concerns Reperformance and adversarial audit test cases, which is a related but different AI governance concern. For this situation: A credit AI's subgroup error rises gradually but standard dashboards only show one combined monthly average.
D:For this situation: A credit AI's subgroup error rises gradually but standard dashboards only show one combined monthly average.
Question 1125
An independent AI auditor reviews this case: An audit script fits a trend to five noisy observations and declares a permanent control breakdown. What is the MOST appropriate risk-based audit recommendation that addresses the root control weakness? Select ONE best answer.
- Document reproducible extraction, definitions, feature joins, calculations and review of exceptions.
- Validate audit-tool outputs against independent truth, monitor drift and use human judgment for material findings.
- Convert any unusual dashboard trend directly into a confirmed AI control failure finding.
- Use context-aware segment and time analysis with corroboration, uncertainty and appropriate baseline comparisons.
Explanation
Correct Answer
D:The reason it is necessary is: An anomaly is a hypothesis requiring data quality and causal investigation, not automatic proof of a control failure. This is the proportionate control response to Audit analytics drift and anomalous trend interpretation: Use context-aware segment and time analysis with corroboration, uncertainty and appropriate baseline comparisons.
Incorrect Answers
A:This option concerns Reproducible audit data transformations, which is a related but different AI governance concern. The audit must corroborate: Inspect seasonality, cohort mix, outliers, confidence intervals, drift metrics and independent transactions.
B:This option concerns Validation of AI-enabled audit analytics tools, which is a related but different AI governance concern. The decisive principle here is: An anomaly is a hypothesis requiring data quality and causal investigation, not automatic proof of a control failure.
C:This attractive shortcut does not resolve the Audit analytics drift and anomalous trend interpretation weakness: Convert any unusual dashboard trend directly into a confirmed AI control failure finding. In this case: An audit script fits a trend to five noisy observations and declares a permanent control breakdown.
Question 1126
A governance and assurance review uncovers the following: An audit script fits a trend to five noisy observations and declares a permanent control breakdown. Which principle BEST explains why the observed practice is a material governance or control concern? Select ONE best answer.
- An anomaly is a hypothesis requiring data quality and causal investigation, not automatic proof of a control failure.
- Convert any unusual dashboard trend directly into a confirmed AI control failure finding.
- AI in the audit process introduces its own reliability and confidentiality risks that must be controlled.
- AI-assisted audit planning can improve coverage but retains risks of confidentiality, bias and fabricated conclusions.
Explanation
Correct Answer
A:The acceptable verified outcome is: Audit analytics identify defensible exceptions while avoiding unsupported causal and discriminatory conclusions. Independent audit evidence includes: Inspect seasonality, cohort mix, outliers, confidence intervals, drift metrics and independent transactions.
Incorrect Answers
B:This attractive shortcut does not resolve the Audit analytics drift and anomalous trend interpretation weakness: Convert any unusual dashboard trend directly into a confirmed AI control failure finding. For this situation: An audit script fits a trend to five noisy observations and declares a permanent control breakdown.
C:This option concerns Validation of AI-enabled audit analytics tools, which is a related but different AI governance concern. For this situation: An audit script fits a trend to five noisy observations and declares a permanent control breakdown.
D:This option concerns Using AI during audit engagement planning, which is a related but different AI governance concern. The audit must corroborate: Inspect seasonality, cohort mix, outliers, confidence intervals, drift metrics and independent transactions.
Question 1127
A risk-based audit engagement examines this operating condition: An audit script fits a trend to five noisy observations and declares a permanent control breakdown. What evidence should the auditor examine FIRST to substantiate or challenge the control owner’s claim? Select ONE best answer.
- Inspect source test inputs, environment version, expected result, output logs and exception handling.
- Inspect seasonality, cohort mix, outliers, confidence intervals, drift metrics and independent transactions.
- Review challenge samples, model changes, error rates, reviewer overrides and data privacy restrictions.
- Convert any unusual dashboard trend directly into a confirmed AI control failure finding.
Explanation
Correct Answer
B:The reason it is necessary is: An anomaly is a hypothesis requiring data quality and causal investigation, not automatic proof of a control failure. The corrective action is: Use context-aware segment and time analysis with corroboration, uncertainty and appropriate baseline comparisons.
Incorrect Answers
A:This option concerns Reperformance and adversarial audit test cases, which is a related but different AI governance concern. The audit must corroborate: Inspect seasonality, cohort mix, outliers, confidence intervals, drift metrics and independent transactions.
C:This option concerns Validation of AI-enabled audit analytics tools, which is a related but different AI governance concern. The audit must corroborate: Inspect seasonality, cohort mix, outliers, confidence intervals, drift metrics and independent transactions.
D:It misses the key control principle: An anomaly is a hypothesis requiring data quality and causal investigation, not automatic proof of a control failure.
Question 1128
An audit committee asks for a defensible assessment of this situation: An audit script fits a trend to five noisy observations and declares a permanent control breakdown. After management addresses the issue, which result MOST convincingly demonstrates effective remediation? Select ONE best answer.
- Audit analytics identify defensible exceptions while avoiding unsupported causal and discriminatory conclusions.
- End-to-end reconciliations explain missing and duplicated records before sampling and metrics.
- The plan covers material high-risk deployments and states documented scope boundaries and assurance limitations.
- Convert any unusual dashboard trend directly into a confirmed AI control failure finding.
Explanation
Correct Answer
A:The reason it is necessary is: An anomaly is a hypothesis requiring data quality and causal investigation, not automatic proof of a control failure. Independent audit evidence includes: Inspect seasonality, cohort mix, outliers, confidence intervals, drift metrics and independent transactions.
Incorrect Answers
B:This option concerns Audit data completeness and reconciliation, which is a related but different AI governance concern. The decisive principle here is: An anomaly is a hypothesis requiring data quality and causal investigation, not automatic proof of a control failure.
C:This option concerns Risk-based AI audit universe and scope, which is a related but different AI governance concern. The audit must corroborate: Inspect seasonality, cohort mix, outliers, confidence intervals, drift metrics and independent transactions.
D:For this situation: An audit script fits a trend to five noisy observations and declares a permanent control breakdown.
Question 1129
During an AI controls assessment, the team learns that an audit firm uses a chatbot to classify thousands of audit exceptions without checking false negatives. What is the MOST appropriate risk-based audit recommendation that addresses the root control weakness? Select ONE best answer.
- Validate audit-tool outputs against independent truth, monitor drift and use human judgment for material findings.
- Treat a high AI confidence score as a substitute for independent audit evidence.
- Reconcile source populations, failed records, joins and transformations before interpreting AI audit analytics.
- Require action owners, committed dates, independent post-change tests and residual-risk decisions to close findings.
Explanation
Correct Answer
A:The reason it is necessary is: AI in the audit process introduces its own reliability and confidentiality risks that must be controlled. Independent audit evidence includes: Review challenge samples, model changes, error rates, reviewer overrides and data privacy restrictions.
Incorrect Answers
B:This attractive shortcut does not resolve the Validation of AI-enabled audit analytics tools weakness: Treat a high AI confidence score as a substitute for independent audit evidence.
C:This option concerns Audit data completeness and reconciliation, which is a related but different AI governance concern. It does not establish control effectiveness for Validation of AI-enabled audit analytics tools.
D:This option concerns Management response and remediation validation, which is a related but different AI governance concern. It does not establish control effectiveness for Validation of AI-enabled audit analytics tools.
Question 1130
An independent AI auditor reviews this case: An audit firm uses a chatbot to classify thousands of audit exceptions without checking false negatives. Which TWO complementary elements should the auditor seek: an effective corrective control and the most probative independent evidence? Select TWO answers.
- Validate audit-tool outputs against independent truth, monitor drift and use human judgment for material findings.
- Use context-aware segment and time analysis with corroboration, uncertainty and appropriate baseline comparisons.
- Treat a high AI confidence score as a substitute for independent audit evidence.
- Reconcile AI inventory, data flows, business ownership, complaints, material incidents and risk appetite to audit plan.
- Review challenge samples, model changes, error rates, reviewer overrides and data privacy restrictions.
Explanation
Correct Answers
A:The reason it is necessary is: AI in the audit process introduces its own reliability and confidentiality risks that must be controlled. For this situation: An audit firm uses a chatbot to classify thousands of audit exceptions without checking false negatives.
E:The reason it is necessary is: AI in the audit process introduces its own reliability and confidentiality risks that must be controlled. This evidence directly tests the asserted control for Validation of AI-enabled audit analytics tools: Review challenge samples, model changes, error rates, reviewer overrides and data privacy restrictions.
Incorrect Answers
B:This option concerns Audit analytics drift and anomalous trend interpretation, which is a related but different AI governance concern. It does not establish control effectiveness for Validation of AI-enabled audit analytics tools.
C:This attractive shortcut does not resolve the Validation of AI-enabled audit analytics tools weakness: Treat a high AI confidence score as a substitute for independent audit evidence. For this situation: An audit firm uses a chatbot to classify thousands of audit exceptions without checking false negatives.
D:This option concerns Risk-based AI audit universe and scope, which is a related but different AI governance concern. It does not establish control effectiveness for Validation of AI-enabled audit analytics tools.
