A sensitivity analysis in real estate underwriting changes one or two key inputs, such as the exit cap rate or rent growth, and shows how the value, the returns or the debt coverage move, usually as a grid. Spreadsheet data tables are the standard way to build one; Titleman returns the common grids already wired into a live Excel underwriting model, and a probabilistic modeling add-in fits better if you need probabilities.
Updated 19 October 2026. Published by Titleman, which makes one of the tools compared.
A worked grid: cap rate by NOI
A base case is one guess; the grid shows how wrong it can be before the deal stops working. Value = NOI ÷ cap rate. For example, an illustrative property with a base NOI of 1,000,000 at a 6.0 percent cap:
| NOI \ cap rate | 5.5% | 6.0% | 6.5% |
|---|---|---|---|
| 950,000 (minus 5%) | 17.27M | 15.83M | 14.62M |
| 1,000,000 (base) | 18.18M | 16.67M | 15.38M |
| 1,050,000 (plus 5%) | 19.09M | 17.50M | 16.15M |
Reading it: a half-point move in the cap rate changes the figure by about 1.3 to 1.5 million, more than a 5 percent move in NOI does (about 0.8 million). Against a 16.5 million offer, five of the nine cells clear it; it fails at any 6.5 percent cap, and at 6.0 percent once NOI drops 5 percent. These are indicated values for illustration, not an appraisal.
The grids most teams expect
Exit cap × rent growth against IRR; price × exit cap against IRR or equity multiple; rate × LTV against DSCR for the lender; and for development, hard cost × lease-up pace against return on cost. A grid shows how fragile a result is, not how likely each cell is.
Tools that build them
| Option | Best for | What it does | Where it stops | Pricing model |
|---|---|---|---|---|
| Spreadsheet data tables | Any grid on your own model | Recalculates the output for each pair | Slow on big models; easy to point at the wrong cell | Staff time |
| Lease-by-lease cash flow software | Institutional models | Built-in sensitivity and scenario runs | Needs a full lease-by-lease setup | Software license |
| Probabilistic modeling add-in | Ranges with probabilities | Monte Carlo runs on the model | Results depend on assumed distributions | License |
| ChatGPT-style general assistant | Explaining a grid, drafting formulas | Text and formulas | No model behind it | Per-seat subscription |
| Titleman | A deal model with grids already in it | Live Excel with cap × NOI, exit cap × rent growth, price × exit cap, DSCR at rate × LTV | No probabilities; no buy or sell verdict | Credits per run; ask on a demo |
Where Titleman fits
Send the OM, rent roll and T-12. The underwriting, about 58 minutes at the median on production runs in the 30 days to 18 October 2026, returns a memo and a live Excel model: rent roll to stabilized NOI, debt, returns and the four grids above. Every input shows its source and date, so you can change the exit cap and watch the grid move. To add grids to a model you already own, Titleman's Excel by prompts edits files up to 40 MB and shows each change before applying it. Titleman does not give a final price, and it does not replace a licensed appraisal.
FAQ
What is the difference between sensitivity and scenario analysis?
Sensitivity moves one or two inputs and holds the rest, usually in a grid. A scenario moves several together, such as a downturn case with lower rent, higher vacancy and a higher exit cap.
Which inputs should I test?
The ones with the most uncertainty and effect: usually exit cap, rent growth, vacancy, price, rate and LTV.
How do I build one in Excel?
Use a two-variable data table linked to the output cell, with the two inputs along the row and column and the base case in the middle.
What sensitivities does Titleman include?
Cap rate by NOI, exit cap by rent growth, price by exit cap, and DSCR at rate by LTV, all as live formulas in the underwriting Excel.
Read more: AI real estate underwriting software, what a cap rate is and IRR in real estate. The product: real estate underwriting AI. To see it on your deal, request a demo.