SBA (Small Business Administration) Feasibility Study Consultant

What the Small Business Administration's own data shows

Most consultants describe the SBA loan market from experience. We compute it. The SBA publishes, under the Freedom of Information Act, a loan-level record of every 7(a) and 504 approval: borrower industry, project state, debenture and third-party first mortgage amounts, term, business age, franchise affiliation, and current loan status. It is public domain, it is refreshed quarterly, and almost nobody in the feasibility industry actually reads it. We maintain the full file and recompute our benchmarks on every release.

Headlines from the current release, FY2010 through the March 31, 2026 data date, 504 program:

Methodology and honesty notes: figures are computed from the SBA's 7(a)/504 FOIA dataset, 504 file, as of the March 31, 2026 release, excluding canceled and never-funded approvals except where approval volume is stated. Loan statuses restate as portfolios season, so performance figures are as-of measurements, not lifetime rates. Gas station figures bridge the 2022 NAICS renumbering. Amounts are debentures and first mortgages, not total project cost; borrower equity sits on top.

Project scale by asset class, from the loan file

When a lender asks whether your project is scaled normally for its class, this is the table that answers, computed from funded 504 loans approved FY2021 through FY2025. Combined financing is the third-party first mortgage plus the CDC debenture; equity is additional.

Source: SBA 7(a)/504 FOIA loan-level dataset, 504 file, March 31, 2026 release. Funded loans approved FY2021 through FY2025.

Three things the table tells a borrower before a single projection is written. Hotels are the program's largest real estate class by dollars, with $2.3 billion in debentures over the last five complete fiscal years and a top decile of deals financing $11.5 million or more. Fifty-six percent of recent 504 hotel borrowers carry a franchise flag, so brand economics belong in the study. And medians are medians: a proposal financing at three times its class median is not disqualified, but its study has to explain the distance, and a study that does not know the distance exists cannot.

What actually goes wrong, by the numbers

The reason lenders commission feasibility studies is visible in the performance data. Take the seasoned cohort, 504 loans approved FY2010 through FY2016, and measure what has happened to date:

• 1.85 percent of funded loans program-wide have been charged off. Add purchases and liquidation payoffs and about 3.6 percent went through distress.
• When a 504 debenture is charged off, the median loss is 82 percent of the debenture balance. These credits do not fail politely. Real estate recovery flows first to the third-party first mortgage; the debenture behind it takes the loss nearly whole.

Failure is concentrated exactly where feasibility scrutiny is concentrated. Charged-off share of the seasoned cohort by class:

Source: SBA 7(a)/504 FOIA loan-level dataset, 504 file, March 31, 2026 release. As-of measurements on seasoned loans, not lifetime rates.

The startup concentration compounds it. Since FY2018, startups are 50 percent of 504 car wash borrowers, 51 percent of self storage borrowers, 54 percent of RV park borrowers, and 35 percent of hotel borrowers, against 11 percent program-wide. Special purpose real estate, no operating history, 25-year money: that is the exact intersection where SOP 50 10 8 expects the lender to hold independent support for the projections, and it is most of what we do.

A borrower can read this table two ways. As a warning, which it is. Or as the outline of the credit conversation before it happens: your lender knows these base rates, priced or declined against them for years, and a study that engages them directly, showing why this project sits on the survivor side of its class distribution, is worth more than one that pretends the distribution does not exist.

Why lenders and CDCs ask for a study

SOP 50 10 8 does not carry a checklist line saying "order a feasibility study." It requires the participating lender to underwrite prudently, as it would without the guaranty, and to document how it satisfied itself on repayment. Where repayment rests on projections rather than history, the projections need independent support, and the feasibility study is how that support enters the file. In practice the request arrives when:

• the borrower is a startup or under two years old, which the data above shows is the norm rather than the exception in car wash, storage, RV park and hotel deals;
• the project is ground-up construction or a major expansion, so history does not carry forward;
• a change of ownership projects performance above the seller's record, and the increment is the whole credit question;
• the property is special purpose, with few alternative users if the operation fails;
• the operation is management-dependent or the operator is new to the field.

The cheapest moment to commission the study is while the application is being assembled. After underwriting raises the question, a number has usually been circulated already, and the honest study must confirm it or contradict it in front of the lender. Your lender or CDC is the authority on whether your file needs one, and we will speak with them before you engage us, free.

The 504 structure, as the data shows it

The textbook 504 is fifty-forty-ten: a third-party lender takes a first mortgage at about half of project cost, the CDC debenture funds about forty percent, and the borrower injects the rest. The loan file confirms the textbook: across funded FY2021-2025 loans, the median third-party first mortgage is 55 percent of the combined financing, with the debenture at 45, and equity on top. The injection rises for startups and for special purpose property, which the next section prices out.

For 7(a), the FOIA file is thinner on real estate specifics, since the program spans working capital, acquisition and construction in one dataset without a use-of-proceeds field. What the study has to prove there is different in kind: operating projections, management capability, and global cash flow sweeping the guarantors' full obligations, tested at the threshold in your lender's credit policy. We prepare both, and the certification names the program and the intended users.

Special purpose property, priced out

A special purpose property has few alternative users if the current operation fails. Hotels, car washes, gas stations, self storage, senior care, marinas, bowling, wineries: the left half of the tables above. The designation does three concrete things to a 504 file.

It raises the equity injection. The standard borrower contribution is 10 percent of project cost, rising to 15 percent for a startup or for special purpose property, and to 20 percent when both apply. On the median recent hotel deal in the scale table, moving from 10 to 20 percent is roughly an additional half million dollars of cash at closing, decided by a classification many borrowers first hear about in underwriting.

It changes the appraisal. Going-concern assets get value allocated among real estate, equipment and intangibles rather than blended, because no one lends against a blend.

It moves the credit weight onto the market evidence. A generic flex building has an alternative-use fallback; a five-bay tunnel's fallback is another tunnel operator. Combine that with the startup shares above and you have the reason this category draws the SBA's heaviest feasibility scrutiny, and why it is our core territory rather than our exception.

How the data enters your study

The loan file is the frame, not the study. Around it, every engagement builds the evidence the reviewer actually has to weigh:

Positioning.

Your project's financing, cost and scale placed against its class distribution from the scale table, so "reasonably scaled" is a computed statement with a percentile attached, not an adjective.

Base rates engaged.

The class performance record acknowledged and answered: what, specifically, places this project outside its class's failure pattern. Site, operator, structure, contracts, brand.

Demand from primary data.

Trade area defined and defended; demand built on the accepted method for the asset class, from traffic counts, demographics, workforce flows and a physically measured competitive inventory, with the arithmetic shown; franchise projections tested against the system's own Item 19 disclosures.

A model built for audit.

Ten years, monthly through the ramp, no hardcoded value in any calculation cell, every input sourced, coverage tested at the threshold your institution applies, operating and global, before and after replacement reserves, under sensitivity, rate stress and simulation.

Conditions named.

Whatever the deal still needs, an executed franchise agreement, a permit, a named manager, a curb cut, is listed with its curing document, which becomes the closing checklist.

A note on coverage ratios

Some firms advertise that every study proves 1.15x operating and 1.00x global coverage. As a buyer, read the second number again: a global test passing at 1.00x passes when the borrower and guarantors have exactly zero margin across everything they owe, and no committee reads that as a pass.

Universal advertised ratios mean the consultant chose the threshold that flatters the study. Thresholds belong to your lender's credit policy, your CDC and the program; they vary; and they are commonly stricter than any floor. We ask for the term sheet first and test at the number your file will actually be measured against, shown year by year, both coverage definitions, before and after reserves.

What you receive

A complete analytical report: conclusion on page one, market and demand analysis with the arithmetic visible, the data positioning described above, competitive supply physically inventoried, site and technical review, management assessment, full projections and stress battery, itemized conditions precedent, sources appendix, and a certification stating plainly that the study is not an appraisal and contains no opinion of value. Plus the fully linked model itself, and reviewer support through closing included in the fee: when your underwriter has a question in month three, we answer it. Standard delivery runs in business days from complete data; rush for files already in underwriting at a fixed add-on quoted up front.

The engagement

1. One.Send the project, program, lender and deadline. Fixed written fee within one business day, free, with the lender call if you want it.
2. Two.A document request tailored to the deal goes out day one: term sheet, budget and sources and uses, site plan, plans or contractor estimate, resumes, historicals where they exist, franchise or operating agreements, purchase agreement on a change of ownership.
3. Three.Market, data positioning and technical analysis.
4. Four.Model, stress, reconciliation, and a check against the program's requirements before anything leaves the building.
5. Five.Delivery and reviewer support through closing.

Independence, and what this document is not

The fee is fixed before work begins, never a percentage of the project, never contingent on the finding, and a conclusion is never revised under pressure. The study names its intended users and is written for them even when the borrower pays. It is not an appraisal, contains no opinion of value, is not prepared under USPAP, and cannot satisfy an appraisal requirement. It is not a business valuation. It does not determine SBA eligibility, which rests with the lender and the Agency. It informs a credit decision rather than making one. All of this appears on page one of every study we sign.

Who prepares your study

Feasibility Study Consultant is a commercial real estate consulting practice specializing in independent, lender-facing feasibility studies for SBA and USDA guaranteed credits and conventionally financed projects. The team that writes our studies is the team that maintains our data infrastructure, including the full SBA loan-level file behind every number on this page, a national parcel corpus, aerial imagery, traffic counts and CMBS property-level performance data. That is why our benchmarks are computed rather than described. Our analysis has been cited by Forbes, The Washington Post, The Independent and Commercial Observer.

More about the practice

Frequently asked questions