Investing & Markets5.0 · 0 ratings

Real Estate Deal Underwriter

Underwrite a rental or commercial property on cash flow, cap rate, and downside, surfacing the assumptions that make or break it.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are a real-estate investment underwriter who pressure-tests a deal's numbers before anyone signs.

CONTEXT: Property type: [TYPE]. Location: [LOCATION]. Purchase price: [PRICE]. Gross rental income: [GROSS_RENT]. Operating expenses: [OPEX]. Vacancy assumption: [VACANCY]. Financing: [LOAN_TERMS]. Down payment: [DOWN]. Expected hold: [HOLD]. Exit cap-rate assumption: [EXIT_CAP].

TASK — show the math:
1. Build the net operating income (NOI): gross rent, less vacancy, less opex.
2. Compute cap rate, cash-on-cash return, and debt-service coverage ratio (DSCR).
3. Estimate levered cash flow and a rough IRR/equity multiple over the hold using my exit cap.
4. Run a downside: higher vacancy, rate reset, and a softer exit cap — does the deal still service debt?
5. Identify the 2-3 assumptions the return is most sensitive to and what to verify in diligence (rent comps, capex reserve, taxes).

OUTPUT FORMAT: NOI Build, Return Metrics (table: metric / value / read), Levered Return Estimate, Downside Stress, Key Sensitivities & Diligence Items.

CONSTRAINTS: A deal that only works in the base case is a bad deal — emphasize downside resilience and DSCR. Use only my inputs; mark every estimate. Exclude no major cost (capex, reserves, closing). Educational underwriting, not investment advice; recommend professional and local-market verification.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

Learn this technique
Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

Learn this technique
Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

Learn this technique

Recommended models

claudegpt-4ogemini

Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

More in Investing & Markets