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

Where AI Enters Finance: Close, Forecasting, Payables and Reporting

Quiz: Where AI Enters Finance: Close, Forecasting, Payables and Reporting

Why Financial Reporting Sets a Higher Bar on Automated Output

Quiz: Why Financial Reporting Sets a Higher Bar on Automated Output

Internal Control Over Financial Reporting When AI Is in the Chain

Quiz: Internal Control Over Financial Reporting When AI Is in the Chain

Audit Trails: Reconstructing How a Number Was Produced

Quiz: Audit Trails: Reconstructing How a Number Was Produced

Using Language Models on Contracts, Invoices and Disclosures

Quiz: Using Language Models on Contracts, Invoices and Disclosures

Extraction Errors and the Checks That Catch Them

Quiz: Extraction Errors and the Checks That Catch Them

Forecasting Models: Assumptions, Drift and Honest Ranges

Quiz: Forecasting Models: Assumptions, Drift and Honest Ranges

Fraud Detection Models and the Cost of False Positives

Quiz: Fraud Detection Models and the Cost of False Positives

Segregation of Duties When an Agent Can Move Money

Quiz: Segregation of Duties When an Agent Can Move Money

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Quiz: Forecasting Models: Assumptions, Drift and Honest Ranges

AI Training for Finance Professionals: Controls, Audit Trails and Numbers You Can Sign
Forecasting Models: Assumptions, Drift and Honest Ranges
Quiz: Forecasting Models: Assumptions, Drift and Honest Ranges

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Question 1 of 5

1. Question

What is the key assumption underlying all statistical forecasting models?

That the future will be chaotic and unpredictable
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That historical patterns will persist (stationarity)
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That human judgment is never correct
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That forecasts should be point estimates with no range
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Question 2 of 5

2. Question

What is drift in a forecasting model?

An error in data entry
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A gradual or sudden decline in model accuracy because the environment has changed since the model was trained
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A temporary glitch in the computer system
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Something that cannot be detected
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Question 3 of 5

3. Question

How should a financial forecast be presented to decision-makers?

Always as a single point estimate with no uncertainty
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As a range with confidence interval, not a point estimate
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As purely qualitative narrative without numbers
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Using only the model vendor's recommendation
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Question 4 of 5

4. Question

What should be documented when a forecasting model is deployed?

Only the model vendor's name
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The assumptions the forecast rests on (stable pricing, customer mix, etc.) so that when assumptions change, the forecast's reliability can be reassessed
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No documentation is necessary
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Only the most optimistic scenario
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Question 5 of 5

5. Question

What is an appropriate retraining cycle for a financial forecasting model?

Never retrain, once trained the model is permanent
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Every week, to capture all new data
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Quarterly, using all historical data, comparing new model accuracy to old on a hold-out test set
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Only when the external auditor asks
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