Financial Model Review

Problem

A model can look polished and still be dangerous. This skill reviews whether the assumptions, structure, scenarios, and logic are strong enough to support a real decision.

Audience

• Primary: investors, diligence teams, and finance-heavy reviewers
• Secondary: operators reviewing planning or fundraising models

When to Use

• Reviewing a startup, deal, or operating model before using it in a memo or decision
• Stress testing growth, margin, burn, or pricing assumptions
• Looking for missing scenarios, broken logic, or false precision
• Translating a spreadsheet into a model review memo with clear verdicts

When Not to Use

• Building a model from scratch
• Market or competitor research without a model artifact
• Drafting the final memo when the model review is only one input: use deal-memo-drafting
• Synthesizing many mixed source documents: use research-synthesis

Required Context

Gather or confirm:

• the model itself, or a faithful export of its assumptions and outputs
• what decision the model supports
• the business model and revenue engine
• the main value drivers or operating levers
• the time horizon
• whether the user wants an investor or operator framing

Useful but optional:

• prior versions, management guidance, or historical notes from Open Brain

Process

1. Frame the review.
   • State the decision the model is being used for.
   • State whether the standard is investor-grade, board-grade, or internal planning.
2. Identify the model shape.
   • Revenue model, cost structure, cash runway, valuation, scenario design, and outputs.
3. Review assumptions.
   • Look for unsupported growth, margin leaps, pricing optimism, CAC efficiency, churn stability, and timing shortcuts.
4. Review structure and logic.
   • Flag missing drivers, circular reasoning, hidden hard-codes, inconsistent periods, or unsupported roll-forwards.
5. Review scenarios.
   • Check whether the model includes downside cases, key sensitivities, and break conditions.
6. Convert the review into judgment.
   • Distinguish fatal issues, caution flags, and acceptable simplifications.
7. Optionally use Open Brain.
   • Search for prior model assumptions, earlier reviews, or management claims.
   • Capture the final review memo or most important flags after completion.

Evidence and Judgment Rules

• Prefer model evidence, historicals, source data, and management guidance over opinion.
• Do not pretend to verify formulas you cannot see. Say what is visible and what is not.
• Label unsupported assumptions as unsupported, not wrong by default.
• Call out where a model is useful for direction but not defensible for high-stakes precision.
• Always note missing scenarios if the downside case is absent or weak.
• Separate structural risk from business risk.

Output

Default output:

• review objective and overall verdict
• key assumptions under pressure
• structural and scenario red flags
• what the model is good enough for
• what must change before the model supports a stronger decision

Works Well With

• competitive-analysis when market benchmarks should inform assumption realism
• research-synthesis when the review needs source-backed contradiction handling
• deal-memo-drafting when the final deliverable needs an economics or risk section

Notes

• This skill reviews what exists. It should not quietly turn into model building.
• The best outcome is a more decision-useful model, not a longer spreadsheet critique.