For Lenders

Know if a Deal Fits
Before You Open the Files

You know your credit box: the property types, geographies, loan sizes, and LTV limits you will lend on. Define those criteria once in Groundstone. When a deal comes in, instantly see if it matches before an analyst spends a minute on it.

The Manual Screening Problem

Every deal that hits your desk gets some attention. Even the ones that never had a chance of closing.

Analyst Time Spent on Non-Starters

An analyst opens the package, reads through the summary, pulls some numbers, then realizes it is a property type you do not lend on. Or the LTV is 85% when your max is 75%. Time burned.

Good Deals Delayed by Bad Ones

When your team processes deals first-in-first-out, a perfect deal can sit behind three non-starters. By the time you get to it, the sponsor has already gone with another lender.

No Consistent Criteria Application

One analyst might know you do not do hospitality. Another might not. Criteria lives in peoples heads instead of a system. Deals slip through or get rejected inconsistently.

Define Your Credit Box Once

Set up your lending criteria in Groundstone. When deals come in, AI extracts the key parameters and matches them against your box. You see the result before anyone reviews.

1

Define Your Criteria

Set your credit box: property types, geographies, loan sizes, LTV/LTC limits, DSCR minimums, sponsor net worth requirements. Set these once and update as your appetite changes.

2

Upload Incoming Deals

When a new deal comes in, upload the package. Groundstone extracts the property type, location, loan amount, LTV, and other key parameters automatically.

3

See the Match Score Instantly

Before anyone reviews, you see: "This deal matches 8 of 10 criteria" or "This deal fails on LTV and geography." Decide in seconds whether it is worth pursuing.

Credit Box Criteria

Define the parameters that matter for your lending program. AI extracts these from each deal and scores the match.

Property Type

  • Multifamily, office, retail, industrial
  • Hospitality, self-storage, mobile home
  • Mixed-use, special purpose
  • Set include or exclude lists

Geography

  • States, MSAs, or counties
  • Primary, secondary, tertiary markets
  • Urban, suburban, rural
  • Flood zone or disaster risk limits

Loan Size

  • Minimum loan amount
  • Maximum loan amount
  • Sweet spot range
  • Per-unit or per-SF thresholds

Financial Metrics

  • Max LTV or LTC
  • Min DSCR
  • Debt yield minimum
  • Occupancy thresholds

Sponsor Requirements

  • Minimum net worth
  • Liquidity requirements
  • Track record (units owned, years)
  • Recourse vs. non-recourse eligibility

Deal Type

  • Acquisition, refinance, construction
  • Bridge, permanent, mezz
  • Stabilized vs. value-add
  • Ground-up vs. renovation

What You See

For every deal uploaded, you get an instant credit box match before anyone reviews.

Credit Box Match Report

Instant scoring against your defined criteria

Sunrise Apartments - Dallas, TX
240-unit multifamily acquisition
8/10
Criteria Match
Property Type: Multifamily Match
Geography: Dallas-Fort Worth MSA Match
Loan Size: $18.5M Match ($5M-$50M)
LTV: 72% Match (Max 75%)
DSCR: 1.28x Match (Min 1.20x)
Occupancy: 94% Match (Min 90%)
Sponsor Net Worth: $8.2M Match (Min $5M)
Sponsor Experience: 850 units Match (Min 500)
Recourse: Requesting non-recourse Requires Review
Property Age: 1978 Prefer post-1990

Why This Matters

Pre-screening lets you prioritize the right deals and pass faster on the wrong ones.

Save Analyst Time

Do not waste 30 minutes reviewing a deal that fails on three criteria. Know instantly.

Prioritize Best Fits

Sort incoming deals by match score. Jump to the ones that fit your box perfectly.

Consistent Application

Your criteria applied the same way every time. No deals slipping through or getting rejected wrong.

Stop Reviewing Deals That Never Fit

Define your credit box once. See which deals match before anyone spends time on them. Focus your team on deals that have a real chance of closing.