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AI Training for Finance Professionals: Controls, Audit Trails and Numbers You Can Sign

External Audit Expectations About AI in Finance Processes

Quiz: External Audit Expectations About AI in Finance Processes

Tax, Regulatory Filings and Automated Preparation Risk

Quiz: Tax, Regulatory Filings and Automated Preparation Risk

Confidentiality and Price Sensitive Information in Prompts

Quiz: Confidentiality and Price Sensitive Information in Prompts

Vendor Tools in the Finance Stack and What to Check

Quiz: Vendor Tools in the Finance Stack and What to Check

Documenting AI Use for the Audit Committee

Quiz: Documenting AI Use for the Audit Committee

Building a Finance AI Control Matrix

Quiz: Building a Finance AI Control Matrix

Final exam: AI Training for Finance Professionals: Controls, Audit Trails and Numbers You Can Sign

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Quiz: External Audit Expectations About AI in Finance Processes

AI Training for Finance Professionals: Controls, Audit Trails and Numbers You Can Sign
External Audit Expectations About AI in Finance Processes
Quiz: External Audit Expectations About AI in Finance Processes

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Question 1 of 5

1. Question

What is the difference between deterministic and probabilistic AI systems from an auditor’s perspective?

Both are equally auditable
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Deterministic systems produce the same output for the same input and are easier to test; probabilistic systems require evidence of training on representative data and performance testing
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Probabilistic systems are never used in finance
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Auditors do not distinguish between them
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Question 2 of 5

2. Question

What five questions do external auditors typically ask about AI processes?

Only questions about cost
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Is the model deterministic or probabilistic, who owns it, was it validated on your data, what exception cases does it struggle with, and how is performance monitored in production
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Auditors do not ask about AI
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Only technical questions about code
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Question 3 of 5

3. Question

What governance documentation should you maintain for an AI system used in financial reporting?

No documentation is necessary
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Who approved AI use, training data and process, testing results, deployment parameters, monitoring metrics and any incidents or retraining
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Only the vendor's documentation
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Documentation only if an error occurs
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Question 4 of 5

4. Question

How should control intensity match the AI system’s risk?

All AI systems should have the same heavy controls
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Controls should be proportionate to risk: light controls for non-material applications, heavy controls for material ones
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Low-risk systems do not need any controls
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Only material systems need controls
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Question 5 of 5

5. Question

When should you discuss AI implementation with your external auditor?

Never discuss it before deployment
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After deployment, when auditor questions arise
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Before deployment, so the auditor understands your control plan
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Only if the auditor specifically asks
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