1. Assumption name and purpose
State what the assumption represents and which model mechanics or decisions it affects.
2. Source and method
Document whether the value comes from experience, external data, contract terms, expert judgment, regulation, market data, or another source.
3. Owner and approver
Identify who proposes, reviews, approves, and maintains the assumption.
4. Effective date and version
Record the period the assumption applies to and which model version uses it.
5. Sensitivity and materiality
Describe how model outputs respond to reasonable changes and whether the assumption is material to the decision.
6. Limitations and review triggers
Document data limitations, uncertainty, known biases, review frequency, and events that should trigger an earlier review.
Important: The correct actuarial, legal, regulatory, privacy, security, accounting, or other specialist review depends on the actual use case and jurisdiction.
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