Seasonality in SBA Cash Flow | Outsourcing Processing

Underwriters reject seasonally averaged cash flow projections more often than brokers expect. The reason isn’t the pattern itself—it’s how it’s presented. A contractor who earns $80k in three months and $5k in the other nine won’t qualify with a flat $27k/month projection, even though the total is mathematically correct. Lenders want to see the actual seasonal shape reflected in your projection, documented clearly enough that the file reviewer can follow the logic without asking questions. This article walks through how to build a defensible seasonal projection for Form 1919 and explains the specific techniques underwriters are trained to accept.

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Why a Flat Average Fails Underwriter Review

Seasonal businesses report historical cash flow that rises and falls predictably. A pool service might earn nothing November through February, then ramp to $15k/month May through September. A tax prep firm sees nearly all revenue January through April. A Christmas decoration installer pulls $60k in October and November, breakeven the rest of the year.

When a broker submits a flat monthly projection—say, $25k every month for 12 months—underwriters flag it as unrealistic because it contradicts the business’s own tax returns. The underwriter’s job is to confirm that the projected cash flow aligns with what the applicant actually demonstrated they could earn. If the historical tax data shows revenue clustering in certain months, a monotone projection signals either insufficient documentation or a misunderstanding of the borrower’s operating pattern. That creates friction and slows approval.

The solution is to project the seasonality that already exists in the tax data, not smooth it away.

Three Methods for Reflecting Seasonal Patterns

Method 1: Strict Historical Replication

The simplest and often most defensible approach is to project the exact seasonal pattern the borrower demonstrated in recent years. Extract monthly revenue (or draw, or net profit) from the last 24 months of tax records—either 1099s if available or Schedule C if self-employed—and plug that month-by-month pattern into the 12-month projection period.

Example: A 1099 sub-contractor earned the following over the last 24 months:

Months 1–2: $8k each month
Months 3–6: $22k each month
Months 7–9: $28k each month
Months 10–12: $12k each month

Replicate this exact pattern into the 12-month projection on Form 1919. Month 1 projects to $8k, month 2 projects to $8k, and so on. The total is $240k, the same as the historical 24-month average. Underwriters rarely object because the borrower’s own tax records prove they can achieve those numbers.

Strength: Directly anchored to filed tax returns; minimal rebuttal risk.

Weakness: If the borrower had an unusually bad or good year, replication can lock in an outlier. If January was a $5k anomaly but December of the previous year was $20k, you might want to weight both to avoid over-penalizing or over-rewarding the projection.

Method 2: Averaging Within Seasonal Bands

For borrowers with multi-year tax data and some year-to-year volatility, segment the 12-month cycle into high, medium, and low seasons, then average revenue within each band. This smooths short-term noise while preserving the seasonal shape.

Example: A seasonal contractor with three years of data:

High season (June–August): Year 1 earned $26k, Year 2 earned $29k, Year 3 earned $24k. Average: $26.3k per month.
Medium season (April–May, September–October): Year 1 earned $15k, Year 2 earned $17k, Year 3 earned $14k. Average: $15.3k per month.
Low season (November–March): Year 1 earned $4k, Year 2 earned $5k, Year 3 earned $3k. Average: $4k per month.

The projection becomes: June–August each get $26.3k, April–May and September–October each get $15.3k, and November–March each get $4k. Total annual: $216.7k, close to the three-year average but shaped to match the borrower’s actual earning cycle.

Strength: Balances historical anchoring with reasonable smoothing; shows sophisticated, multi-year analysis that underwriters respect.

Weakness: Requires clean multi-year data. Doesn’t work well for young businesses or those with dramatic swings in season length or intensity.

Method 3: Conservative Replication with a Written Explanation

If the borrower’s most recent year was atypical—a new contract began, a seasonal worker was hired mid-year, or a major client was lost—replicate the historical pattern but attach a brief dated memo explaining the adjustment and why it reflects expected future performance more accurately than the prior-year shape.

Example: A 1099 electrician’s 2024 Schedule C shows: January $6k, February $4k, March $8k, April $16k, May $18k, June $22k, July $25k, August $21k, September $14k, October $10k, November $7k, December $5k. The borrower landed a new industrial contract in April 2024 that runs year-round. The broker’s memo states: “Months 1–3 reflect pre-contract revenue; months 4–12 reflect the blended revenue after the April contract start and are expected to repeat in 2026. Projections use the April–December 2024 average ($14.6k/month) for the first three months of 2026, then revert to the historical cycle for months 4–12, on the basis that the new contract has been in place for [X months] and is expected to continue.”

This approach gives underwriters a clear reason why the projection differs from raw historical replication, and it demonstrates that the broker understands the borrower’s business.

Strength: Flexible; accommodates changing circumstances with documentation.

Weakness: Requires credible explanation. Unsupported adjustments invite skepticism.

Documenting the Seasonal Pattern on Form 1919

The 1919 itself has a 12-month line and a total. The form doesn’t have a dedicated “seasonality note” field, so the documentation must sit in your transmittal memo or in a separate attachment labeled “Cash Flow Projection Methodology.”

Your memo should include:

The source of historical data (last 24 months of Schedule C, 1099s, bank statements, or all three).
The specific method used (replication, banding, or adjusted replication).
A side-by-side table showing the last 12 months of actual revenue and the projected 12 months, so the underwriter can see the comparison at a glance.
If banding: the definition of each season and the rationale (e.g., “high season aligns with school calendar” or “low season reflects holiday closures”).
Any major changes in the business (new contracts, staffing, service offerings) and how they affect the projection.

Underwriters need to trace your logic in under 90 seconds. A clear memo reduces friction and accelerates approval.

Common Seasonality Patterns and How Lenders View Them

Flat or near-flat revenue: If the borrower’s actual tax data shows minimal seasonal swing (variation under 15% month-to-month), a flat projection is defensible. Your memo might say: “Borrower’s revenue is consistent year-round (range: $8.2k–$9.1k/month); projection reflects this stability.”

Single peak (one or two high months): Tax prep, holiday services, and event-based businesses see one pronounced spike. Replicate it exactly. If the peak is in January, January projects high; if it’s December, December projects high. Underwriters expect this and will question a flat $30k/month for a firm that earned $120k in December and $2k in the other 11 months.

Multiple peaks: Contractors, landscapers, and freight brokers often see two or three high-revenue windows (e.g., spring cleanup and fall maintenance for landscapers). Segment your seasonal bands accordingly, and your memo can cite the natural business cycle.

Trending upward or downward: If historical revenue has climbed month-to-month or year-to-year, underwriters will ask if the borrower expects that trend to continue. If yes, projecting a flat average understates the likely outcome, and your memo should explain why. If the trend is expected to stabilize, say so explicitly. A borrower who grew from $5k/month to $15k/month over 24 months and now stabilizes at $15k is different from one climbing into year two of a startup. Your documentation clarifies which scenario applies.

DSCR Calculation and Seasonality

Once the seasonal projection is in place, DSCR calculation becomes mechanical—but the seasonal shape affects how underwriters interpret the result. If the projection shows a $5k/month low season, the underwriter will pay close attention to whether debt service falls due in that window. If principal and interest payments are front-loaded (as SBA loans sometimes are), a borrower with projected $5k/month in the low season and $200k debt service due in month three faces a tough file, even if total annual cash flow is strong.

This is where detailed seasonal documentation pays off. When an underwriter sees your memo laying out the exact seasonal pattern and the borrower’s reserves or working capital, the underwriter can assess real cash flow stress, not just an annual average.

Pitfalls to Avoid

Don’t project revenue growth without justification. If the borrower grew 20% last year and you project 20% growth again without explanation, the file can be flagged for unsupported assumptions. If the growth is tied to a new contract or market expansion that is documented in the application, reference it. If it’s aspirational, don’t project it on Form 1919.

Don’t flatten seasonality if it’s not there. The surest way to create underwriter pushback is to report $200k in actual annual revenue with seasonal swings and then project it as $16.7k/month, which is a red flag for inflation or misunderstanding.

Don’t ignore multiple revenue streams. If the borrower earns income from two or more sources with different seasonal patterns, project each separately, then add them. A contractor with a W-2 day job (flat $5k/month) and 1099 side work (seasonal) should show both on the 1919, with a clear note that they are combined.

Don’t submit the 1919 without a transmittal memo that explains seasonality. Underwriters are trained to spot seasonality and will ask if they have to guess at your logic. Pre-emptively document it and you remove a source of delay.

Seasonality and Multiple Years of Tax Returns

The U.S. Small Business Administration’s SBA does not specify a minimum number of years required for seasonal business documentation, and wholesale lender overlays vary. Some lenders require two years of tax returns; others want three. If you have two years of consistent seasonal data, your banding method is stronger than if you have only one.

When data is limited, replication of the most recent 12 months is acceptable, but your memo should note that “only one full year of tax data is available; projection assumes the 2025 seasonal pattern repeats in 2026.” This signals to the underwriter that the file is not incomplete, just constrained by the borrower’s history.

This article is educational and does not constitute lending advice — confirm current SBA program requirements with your lender before submitting a file.

Frequently Asked Questions

What if the borrower’s last year was a major outlier due to a one-time event?

Use the prior-year data instead, or blend both years with a note explaining why. If the outlier was a special project that won’t repeat, project the normal seasonal pattern and document the reasoning. Underwriters understand that a single contract or client loss can distort one year; your job is to show what sustainable cash flow looks like going forward.

Can I project higher revenue than the borrower earned in the prior year if they expect growth?

Only if the growth is documented—new contract signed, new employee hired, expanded territory, etc. Unsupported growth assumptions are rejected. If growth is realistic, replicate the current seasonal shape and apply a growth percentage uniformly across all months, then explain the driver in your memo.

Should I average out seasonal dips to hit a higher DSCR?

No. Averaging out seasonality to inflate the projection is fraud. The underwriter’s job is to confirm that the borrower can service debt every month, not just in aggregate. If the seasonal low is $5k/month and debt service is $8k/month, that’s a real problem the underwriter needs to see and address. Your job is to document the truth clearly.

How detailed should my seasonality memo be?

One page, maximum two. Include: method used, historical data source, side-by-side table of actual versus projected months, and any business changes that affect the projection. Underwriters read files quickly; a dense, multi-page memo gets skimmed. Be concise and clear.

What if the borrower is in their first year of business and has no prior seasonal data?

Use bank deposits, contract schedules, or client agreements to infer the expected seasonal pattern. If January–March is historically slow in that industry (e.g., landscaping), acknowledge it. Provide the borrower’s forecast with supporting documentation (e.g., “Jan–March projected at $8k/month based on current pipeline and seasonal industry norms”). The 1919 still requires 12 months; incomplete seasonality is better than made-up flatness.