Coverage is the number every reviewer turns to first. What it means, how it is built, and why a ratio reverse-engineered to clear a covenant is the fastest way to lose a credit committee.
Debt service coverage ratio is net operating income divided by total debt service for the same period. A 1.25x coverage means the project generates a quarter more cash than it needs to make its payments. Below 1.00x it does not cover them at all.
The arithmetic is trivial. Everything that matters is in the inputs: what counts as net operating income, whose debt service is included, which year is being tested, and whether the revenue behind the NOI is evidenced or assumed. Two studies on the same project can report coverage a quarter-turn apart entirely through defensible-looking choices in those four places — which is why a reviewer reads the build, not the ratio.
Minimums vary. A 1.15x to 1.25x range is common across SBA, USDA and conventional lending, but the operative number is whatever your lender's credit policy says, adjusted for asset class and the risk profile of the sponsor. The study does not set the threshold; it reports where the project lands against the one that applies and how durable that position is.
The single most common defect in a rejected study is a projection built backwards from the required coverage. It is easy to spot: occupancy or capture that sits a few points above every comparable in the market, an expense ratio below the peer set with no operating reason given, a ramp that reaches stabilisation faster than any comparable delivery, and — the giveaway — a stabilised coverage of exactly 1.25x.
Reviewers see hundreds of these. Once the coverage line looks engineered, every other number in the report is read with suspicion, including the ones that were right. The remedy is direction of travel: build the market case first, let the revenue fall out of it, and report the coverage that results. If that number does not clear the covenant, the useful output is the analysis of what would have to change — a smaller building, a longer amortisation, more equity, a different rate assumption — not a quietly adjusted occupancy curve.
Every model we deliver is fully linked with no hard-coded outputs, so the underwriter can change an assumption and watch coverage move. Each study reports coverage by year through the ramp and at stabilisation, under a base case built from the market findings, and under stress cases that flex the variables the specific asset is actually sensitive to — occupancy and rate for lodging, throughput and price for processing, census and payer mix for healthcare, enrolment for schools.
We state the break-even point explicitly: the revenue level at which coverage reaches 1.00x, and the level at which it breaches the covenant. A sponsor and a credit committee should both know that number before signing, and it is the first thing an experienced reviewer looks for.