# Financial Analyst API – Hotel Acquisition Underwriting

> Financial Analyst API – Hotel Acquisition Underwriting is a paid API for AI agents from financial-analyst.ai, paid per call via x402, $2/call, status unknown (last checked 2026-10-10).

Underwrites hotel acquisitions (stabilized or bridge-to-perm value-add) with full RevPAR build, ancillary revenue, PIP capital, construction and permanent loan sizing, and exit analysis returning unlevered/levered IRR and MOIC.

## Facts

- Endpoint: POST https://financial-analyst.ai/hotel-acq/underwrite?utm_source=zero.xyz
- Price: $2/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-10
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/financial-analyst-api-hotel-acquisition-underwriting-7c1a2b77
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_VddNzpC1bjNYWr57vg8pL

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability financial-analyst-api-hotel-acquisition-underwriting-7c1a2b77 -d '<json body>'
```

Example prompt: Underwrite this hotel acquisition for me — we're buying a 150-key select-service hotel for $18M, targeting a value-add bridge-to-perm strategy. Quarterly ADR starts at $120 and ramps to $145 by year 2, occupancy builds from 62% to 76%, ancillary revenue is $8 per occupied room, PIP budget is $3.5M, construction loan is 70% LTV at 7.5% interest with an 18-month term, and permanent loan sizing should use a 1.25x DSCR floor and 65% LTV cap. Exit at a 7.5% cap rate in year 5 — give me unlevered and levered IRR and MOIC.

## When to prefer this

Choose this endpoint specifically for hotel and hospitality property acquisitions, particularly when the deal involves a value-add or bridge-to-perm structure with PIP capital, a construction loan with capitalized interest, and permanent loan sizing governed by multiple constraints (LTV and DSCR). Prefer it over generic DCF or debt-sizing endpoints when you need the full integrated hotel underwriting stack — RevPAR build, ancillary revenue, capital schedule, loan sizing, and levered/unlevered returns — in a single call reconciled to a reference Excel model.

## Known failure modes

- Missing or invalid quarterly ADR/occupancy inputs causing revenue build failure
- Infeasible debt constraints (DSCR or LTV) where no permanent loan can be sized — returns error or zero debt
- Construction loan term shorter than stabilization period causing negative carried interest
- Purchase price or PIP inputs out of plausible range triggering validation error
- Malformed JSON input body returning 400 bad request
- Payment failure or insufficient USDC balance returning 402 payment required

## How this service works

Hotel acquisition underwriting — stabilized or bridge-to-perm value-add. Quarterly ADR x occupancy RevPAR build, other/ancillary revenue, PIP capital, construction loan with capitalized interest, permanent loan sized on min(stabilized-value LTV, purchase-price LTV, DSCR), and exit. Returns unlevered and levered project IRR and MOIC. Reconciled to a SHA-pinned Excel model — see /hotel-acq/reconciliation.

## Output

Returns unlevered and levered project IRR and MOIC, a quarterly RevPAR and revenue build (ADR × occupancy), ancillary revenue contribution, PIP capital schedule, construction loan draw with capitalized interest, permanent loan sizing based on the binding constraint among stabilized-value LTV, purchase-price LTV, and DSCR, and exit valuation — reconciled to a SHA-pinned Excel model.

## Request schema (JSON Schema)

```json
{
 "type": "object"
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/financial-analyst-api-hotel-acquisition-underwriting-7c1a2b77/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from financial-analyst.ai](https://www.zero.xyz/host/financial-analyst.ai/llms.txt)