Methodology & Data Sources

• • Pricing is calibrated against publicly-available rate sheets from six hard money lenders. We blend them rather than copy any single one.
• • Qualification rules come from publicly-available program guidelines for non-QM products (DSCR, bank statement, asset depletion, ITIN, etc.).
• • No lender's internal materials inform our model. Everything is sourced from public marketing pages, third-party comparison sites, or industry data published by organizations like the Mortgage Bankers Association, Case-Shiller, and Zillow Research.
• • Estimates are estimates. Final qualification, rates, and terms come from the lender after underwriting your specific scenario.

Our hard money pricing engine is calibrated against published rate-sheet data from six lenders. Each link below is the public marketing or program page we pulled from:

We also reference Stormfield Capital's published comparison of these lenders for cross-validation of the data.

Each lender has its own cut points: different FICO bands, different experience definitions, different LTC spreads. Copying any single rate sheet would (a) bias toward that lender's specific approach, and (b) break when they update.

Instead, for each parameter (rate range, LTC, LTARV, FICO floor, etc.) we compute a number that:

• • Sits inside the spread of the public lenders' values
• • Doesn't equal any single lender's specific value
• • Is internally consistent (top-tier numbers are always more favorable than bottom-tier)

The result is a four-tier model — premium / strong / standard / limited — based on FICO and recent flip experience, with rate ranges, points, LTC, and LTARV calibrated to industry-typical mid-points.

The non-QM qualifier (the /qualify calculator) is calibrated against publicly-available program guidelines from non-QM wholesale lenders. The underwriting rules in our engine reflect industry-typical cuts on FICO, DTI, DSCR, reserves, and seasoning.

Specific program archetypes we model:

• • Bank statement loans — 12-24 month personal/business statements with industry-typical expense factors
• • DSCR (rental investor) loans — 1.0+ DSCR floor, 75-80% LTV, 660+ FICO
• • Asset depletion / asset utilization — 60-month or 84-month draw-down conventions
• • 1099 / contractor — recent earnings + tenure floors
• • Foreign national / ITIN — typical leverage caps and reserves requirements
• • Recent credit event programs — seasoning windows post-bankruptcy / foreclosure

Our DSCR calculator uses the standard rental-investor formula: monthly market rent ÷ monthly PITIA. The DSCR thresholds (1.0, 1.10, 1.25) and the resulting LTV/rate adjustments are drawn from publicly-disclosed DSCR program matrices. Short-term-rental (STR) DSCR programs typically discount projected revenue and require higher reserves; we surface this as a toggle.

Hard money LTARV caps soften in declining or illiquid markets. We use a coarse state-level adjustment based on publicly-available home-price data:

• • S&P Case-Shiller Home Price Indices for major MSAs
• • Zillow Research home value index for state-level trends
• • FHFA House Price Index for non-major-MSA coverage

We don't use any proprietary or licensed dataset. Coverage is intentionally coarse (state-level rather than ZIP-level) to keep the model defensible from public data alone.

• • We don't pull your credit. You tell us a band; we never check. Real qualification requires a real credit pull from a lender.
• • We don't take referral fees from lenders. Our pricing model isn't biased toward any specific lender or product.
• • We don't claim our estimates are commitments. Every result page says it explicitly: this is an estimate, not a credit decision.
• • We don't replicate any individual lender's rate sheet. The blend is structurally and numerically different from any single source.

The lending market moves. We update our public-source pulls and re-calibrate the blend on a quarterly cadence, or sooner if there's a significant industry-wide shift (e.g., a 100-bps move in benchmark rates). The most recent calibration date is at the top of this page.

If you're a lender and our published assumptions about your program look wrong, email hi@lendqm.com and point us at the correct public source — we'll update.