Draft a risk appetite statement leadership can use
Writes a risk appetite statement with a qualitative stance and measurable limits for each risk category, ready for leadership review.
The prompt
Help me draft a risk appetite statement.
Organization type and size: [e.g. mid-size insurer, SaaS company, hospital, nonprofit]
Strategy and objectives: [what leadership is trying to achieve over the next 3 years]
Risk categories we use: [e.g. strategic, financial, operational, compliance, cyber, reputational, people]
Leadership's views (from interviews or a workshop): [PASTE notes]
Regulatory expectations: [any required elements, or "none"]
Existing limits or metrics: [PASTE]
Produce:
1. Overall statement - 3-5 sentences on how much risk the organization is willing to take in pursuit of its strategy.
2. By category - for each: appetite level (averse / minimal / cautious / open / seeking), a qualitative statement, and 1-3 measurable tolerances or limits. Where I gave no data, write the metric with [SET LIMIT] rather than inventing a number.
3. Zero-tolerance areas stated explicitly (e.g. knowing regulatory breaches, bribery, safety).
4. Tensions - where my leadership notes conflict (e.g. aggressive growth plus minimal operational risk) with questions to resolve them.
5. Governance - who owns it, how breaches of tolerance are escalated, how often it is reviewed.
6. Cascade guidance - how business units should translate it into their own limits.
Plain language a new board member could understand. This is a draft for leadership and board deliberation, not a final position.
Highlighted [brackets] are blanks to replace with your own details.
Fill in the blanks and use this promptMore Legal & Compliance prompts
What to fill in
- e.g. mid-size insurer, SaaS company, hospital, nonprofit
- what leadership is trying to achieve over the next 3 years
- PASTE notes
- any required elements, or "none"
- PASTE
- SET LIMIT
How this prompt is built
This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.
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