DSCR Loan Methodology.

Purpose of this page

Every calculation in every Lendmire article comes from this methodology. We document it publicly because investor lending is too consequential for opaque math. If a Lendmire article tells you a Charlotte property generates $420/mo in cash flow, you should be able to come here, read the assumptions behind that number, and decide for yourself whether the model is reasonable for your situation.

This page is the source of truth. When an article and this page disagree, this page is correct and the article will be updated.

Data sources

Every numerical claim in a Lendmire article traces back to one of five primary sources. We do not invent figures, do not interpolate undocumented assumptions, and do not republish data from secondary aggregators.

Mortgage rate data

The base mortgage rate used across all Lendmire calculations is the 30-Year Fixed Rate Mortgage Average in the United States (FRED series MORTGAGE30US), sourced directly from the Federal Reserve Bank of St. Louis FRED API. FRED republishes the weekly observation from Freddie Mac’s Primary Mortgage Market Survey (PMMS), which is the longest-running mortgage rate index in U.S. real estate (continuous since 1971).

We use this rate as our base because (a) it is independently maintained by the Federal Reserve, (b) it is updated weekly with a clearly documented methodology, and (c) it is the same benchmark that mortgage industry analysts, the Mortgage Bankers Association, and the GSEs use to track the broader rate environment.

State-level property prices and rents

Median property prices and median monthly rents at the state level are embedded in each article at publication and refreshed when state-level housing data is updated by primary sources. Specifically, we triangulate from:

• Property prices: State-level median single-family home prices from the U.S. Census Bureau American Community Survey (ACS) 5-year estimates, cross-referenced with St. Louis FRED state-level house price indices (STATEHPI series family).
• Rental rates: Median gross rent from the U.S. Census Bureau ACS, plus Department of Housing and Urban Development (HUD) Fair Market Rent (FMR) tables for the relevant fiscal year.

For city-level articles, we apply documented research adjustments to the state baseline only when the research process surfaces a credible primary source for that specific market (e.g., a city’s housing department report or a verifiable MLS quarterly summary). Cities without a credible primary source default to the state median.

Property tax rates

State-level effective property tax rates come from Tax Foundation annual state-by-state property tax studies, cross-checked against U.S. Census Bureau state-level property tax data. We use the effective rate (median annual property tax as a percentage of median home value), not the nominal rate.

Insurance rates

State-level homeowner’s insurance rate estimates come from National Association of Insurance Commissioners (NAIC) state-by-state average premium studies, expressed as a percentage of insured value. We use this as a baseline; actual policy quotes vary by carrier, deductible, coverage limits, and property risk profile.

Investor-loan guidelines

DSCR loan qualification thresholds, LTV limits, prepayment penalty structures, and credit minimums are sourced from active wholesale lender guidelines that Lendmire brokers against. These reflect the actual loan programs we close through our wholesale partners, not idealized industry generalizations.

DSCR rate policy

Lendmire’s articles model DSCR rates at the same rate as the conventional 30-year fixed observation (MORTGAGE30US). This is not a placeholder — it is a deliberate policy choice rooted in how DSCR pricing actually works in 2026.

Why DSCR rate ≈ conventional rate (at parity)

In the current rate environment, well-qualified DSCR loans (DSCR ratio ≥ 1.00, credit score 700+, 5-year prepayment penalty) price at essentially the same rate as the 30-year fixed conventional benchmark. The structural premium that DSCR loans carried in earlier cycles has compressed as the DSCR loan market has matured, secondary-market liquidity has deepened, and lender competition has intensified.

This is not a claim that every DSCR loan prices at MORTGAGE30US. It is a claim that the well-qualified scenarios our articles model (the most common investor profile) achieve rate parity. Less-qualified scenarios (lower DSCR, shorter prepayment penalty, lower credit) price higher and our articles disclose this honestly.

Prepayment penalty mechanics

Some states (Illinois, Minnesota, New Mexico, Pennsylvania, Vermont, Virginia, others) have specific restrictions or prohibitions on prepayment penalties for certain loan types. In those states our articles default to the available PPP term, or note that PPP isn’t available, and the actual rate is confirmed during the quote conversation. See your state’s specific limits or speak to a Lendmire DSCR expert.

PITIA calculation

PITIA (Principal, Interest, Taxes, Insurance, plus HOA where applicable) is the standard monthly housing payment used for both DSCR ratio calculations and cash flow analysis. Lendmire articles use the following calculation.

Formula

Defaults used in our calculations

Down payment

20% for DSCR scenarios (standard DSCR purchase minimum). 30% for conventional comparison scenarios to reach rate parity with DSCR (accounts for typical conventional investment-property loan-level pricing adjustments, “LLPAs”).

Loan term

30 years fixed (360 months). This is the most common DSCR product; we also originate 5/6, 7/6, and 10/6 ARMs, plus interest-only structures, but those aren’t the default for article math.

Property tax rate

State-level effective rate from Tax Foundation, applied to property price as a percentage. Articles use the same rate at acquisition and assume it scales with assessed value over time (a simplifying assumption; actual reassessment cycles vary by jurisdiction).

Insurance rate

State-level average from NAIC, applied to property price. We treat insurance as a constant percentage of insured value; actual quotes vary significantly by carrier, coverage, deductible, and risk profile.

HOA fees

Not included in default PITIA. When a specific property carries HOA dues, they should be added on top of the PITIA figure. We exclude them from default math because the median single-family rental in most U.S. markets has no HOA.

PMI

Not modeled. DSCR loans don’t require PMI; conventional investment property at 30% down generally doesn’t either.

DSCR ratio

Debt Service Coverage Ratio (DSCR) measures whether the property’s gross rental income covers its full monthly housing obligation. It is the single most important number in DSCR lending.

What the threshold values mean

DSCR ≥ 1.25

Strong coverage. The property generates 25%+ buffer above debt service. DSCR programs typically apply their tightest pricing tier at this threshold or above.

DSCR ≥ 1.00 (and < 1.25)

Qualifying for most standard DSCR programs. Rent covers PITIA fully. Pricing typically tracks conventional investment-property rates at comparable LTV after standard LLPAs.

DSCR 0.75 – 0.99

“Alt-DSCR” or reduced-LTV territory. Many lenders will still finance these scenarios but typically at lower LTVs (10-15% more down) and/or slightly higher rates.

DSCR < 0.75

“No-ratio DSCR” territory. Financing is still available through specialty programs but requires more equity and accepts more rate premium. These scenarios deserve a real conversation with an expert rather than a generic calculator.

Stress test assumptions

Stress test widgets in Lendmire articles model how a property holds up under adverse conditions. We use deliberately conservative defaults — the goal of a stress test is to identify scenarios where the deal breaks, not to confirm it works in the best case.

Vacancy stress

We model three vacancy levels: 1 month / year (~8.3%), 2 months / year (~16.7%), and 3 months / year (25%). The mild scenario (1 month) approximates a single tenant turnover with a typical 30-day re-rent period. The severe scenario (3 months) reflects a difficult turnover, an eviction situation, or a market with declining demand.

Industry-standard property management assumptions typically use 5-8% vacancy as a baseline. Our stress scenarios are 1.5x to 3x that baseline — explicitly designed to test the deal’s resilience.

Maintenance overrun stress

We model three maintenance levels expressed as a percentage of gross rent: 5%, 8%, and 10%. The mild scenario approximates normal repairs (broken appliance, minor plumbing) over the course of a year. The severe scenario reflects a year with a significant capital expense (HVAC replacement, roof repair, major plumbing).

A common rule of thumb is to reserve 1% of property value annually for maintenance. On a $350,000 property generating $2,000/mo rent, that’s $3,500/yr — which is about 14.5% of annual gross rent. Our 10% stress is therefore reasonable but not extreme.

Rate-at-refi stress

We model three rate scenarios at an assumed 5-year refinance point: +100 basis points, +200 basis points, and +300 basis points above the current observation. This stress tests the assumption that you’ll refinance at a future rate and acknowledges that your refi rate is not guaranteed to be lower than your acquisition rate.

For the refinance simulation, we assume a 75% LTV refinance (industry-standard for DSCR cash-out refi).

Combined worst case

The combined scenario stacks the maximum severity of all three stresses simultaneously. This is intentionally implausible — three simultaneous bad outcomes is rare in practice — but it stress-tests the deal’s worst-case survival.

A property that survives all three stresses with positive cash flow is institutional-grade. A property that survives most but fails the combined scenario is normal — that’s a realistic boundary of what the asset can absorb. A property that fails most individual stresses is leveraged too thinly; small adversities flip it cash-flow negative.

Cash-on-cash return

Cash-on-cash (CoC) return is the metric serious investors actually use to evaluate deals. It measures annual cash flow as a percentage of cash put into the deal.

Cash invested components

Lendmire articles model total cash invested as the sum of three components:

• Down payment — 20% of purchase price for DSCR (the default scenario)
• Closing costs — 3% of loan amount (typical DSCR closing costs include title, escrow, lender fees, recording, and prepaid items)
• Reserves — 6 months of PITIA (typical DSCR lender reserve requirement; conservative end of the 3-6 month industry range)

This understates total cost slightly (we don’t model inspection fees, appraisal cost, or rate-lock extensions) but captures the major components. Real closing costs vary by state, lender, and scenario.

Year 1 vs. 5-year averaged CoC

The Year 1 CoC uses initial rent and initial PITIA — the simplest version of the metric. It is what most investor calculators report.

The 5-year averaged CoC accounts for two compounding effects: rent growth (we assume 3% annual rent growth, the long-term U.S. average) and amortization (you’re paying down principal, which increases your equity). The 5-year averaged number is typically meaningfully higher than Year 1 and is the more honest representation of what a 5-year hold actually yields.

All-in return

The all-in return further adds an assumption of 3% annual property appreciation, which is the long-term U.S. residential real estate average. This is an assumption, not a promise — actual appreciation varies dramatically by market and cycle. We disclose this clearly in every widget.

The all-in return is what serious investors use to compare real estate against other asset classes (stocks, bonds, private equity). On a cash-on-cash basis alone, real estate often looks unimpressive; on an all-in basis (cash flow + amortization + appreciation), it typically reveals its actual long-term return advantage.

Strategy math — LTR / STR / BRRRR

Strategy widgets compare three operational approaches for the same property. Strategy is operational; financing is the same DSCR loan in all three cases. What changes is the layer of operating assumptions on top of the loan.

Long-Term Rental (LTR)

The simplest operating strategy, with the least management overhead of the three. Articles model LTR with these assumptions:

• Gross rent: median state/city LTR rate
• Vacancy: 5% (industry-standard baseline)
• Property management: 8% of gross rent
• Maintenance reserve: 5% of gross rent

Short-Term Rental (STR)

STR economics are highly variable by market, season, property type, and management quality. Lendmire articles use an industry-standard 2.5x multiplier on LTR gross rent as the STR gross revenue estimate. This is a rule of thumb that’s reasonable for many metro markets but can range from 1.5x in low-tourism areas to 4-5x in destination markets (Smoky Mountain cabins, beach properties, ski towns).

Articles model STR expenses with these assumptions:

• Effective vacancy: 30% (accounts for off-season nights and booking gaps)
• Property management: 20% of gross (STR managers charge meaningfully more than LTR PM)
• Cleaning: 8% of gross
• Supplies (consumables, linens, toiletries): 3% of gross

BRRRR (Buy, Rehab, Rent, Refinance, Repeat)

BRRRR is a capital-recycling strategy. Articles model BRRRR with these assumptions:

• Rehab cost: 10% of purchase price (rough estimate; varies enormously by property condition)
• Post-rehab appreciation: 5% above purchase price (assumes rehab adds value)
• Refinance: 70% LTV cash-out refi after 12 months of seasoning
• Ongoing cash flow: LTR economics post-refi

The headline BRRRR number is cash recaptured at refi — the difference between the refi loan amount and the remaining original loan balance. If this exceeds the original cash invested, BRRRR has fully recycled the deal and you can deploy that capital into the next property.

BRRRR is execution-heavy. Rehab budgets routinely overrun, appreciation isn’t guaranteed, and refi rates may be higher when the time comes. Articles use these assumptions as a model; your actual BRRRR economics depend heavily on your rehab discipline, market timing, and refinance environment.

Update frequency & architecture

Lendmire articles are not static. Every dynamic figure (current mortgage rate, cash flow at current rate, DSCR ratio at current rate, related calculations) auto-refreshes on every page load. We call this the Layer 1 / Layer 2 / Layer 3 architecture.

Layer 1 — Bake at publication

When an article is first published, all dynamic figures are computed against the FRED observation at publication time and baked into the published HTML. This ensures the article displays correct numbers immediately — no JavaScript dependency for the first paint, and search engines see real numbers in the served HTML.

Layer 2 — Refresh on page load

A small JavaScript layer runs on every page load. It fetches the current FRED observation, recomputes all dynamic figures with the current rate, and replaces the baked values in place. This happens client-side, typically within ~50ms of page load. Users see refreshed numbers without any visible flicker on most articles.

Layer 3 — Server-side rate proxy

The FRED API has a strict request budget. Lendmire runs a server-side proxy that caches the current observation (refreshed at most twice per 24 hours) and serves it to article visitors. This means a busy day with 100,000 article views still only generates a handful of upstream FRED requests. The architecture is built to scale.

What this means for data freshness

An article published 18 months ago, viewed today, displays today’s mortgage rate, today’s cash flow numbers, and today’s DSCR ratio. The narrative text (the article’s analysis and prose) reflects the conditions at publication, but the live numbers reflect right-now. Lendmire articles are engineered for graceful degradation: if a live data feed is temporarily unavailable, the article cleanly falls back to the publication-time figure. The reader sees a real number either way.

Assumptions & limits

The methodology models market-level economics. Several factors are intentionally out of scope — investor-specific or property-specific variables that no market-level model should claim to capture:

• Local market variance. Our state-level data is a baseline. Charlotte is not the same as Asheville is not the same as Wilmington. City-level data overrides the state baseline where we have it; otherwise we use the state median and disclose this clearly.
• Capital expenditures. Lendmire’s maintenance assumptions (5% of gross rent baseline, 10% stress) cover operating-level maintenance. Major capital events (roof, HVAC, foundation) are modeled separately by serious investors as a dedicated capital reserve — typically 1% of property value annually.
• Tax implications. Articles model gross cash flow. Real estate carries significant tax advantages — mortgage interest deduction, depreciation, 1031 exchange, cost segregation — that improve actual after-tax returns by amounts specific to each investor’s situation. Tax modeling is properly the work of a CPA or tax strategist who knows the investor’s full picture, not a market-level article.
• Insurance variability. We use state averages. High-risk regions (coastal hurricane zones, wildfire-prone areas, hail-belt regions) carry significantly higher insurance costs than state averages reflect.
• HOA fees. Not modeled by default. Add them to PITIA when applicable.
• STR feasibility. Articles model STR economics — gross revenue, expenses, vacancy. The regulatory layer (local STR ordinances, HOA rules, zoning) varies by city and even by neighborhood, and requires verification with the municipality. Regulatory verification is the investor’s responsibility before any STR strategy commitment.
• Appreciation assumption. 3% annual is the long-term U.S. average. Your specific market and cycle will differ — sometimes meaningfully.
• Rate forecasting. Articles use the current FRED observation as the baseline. Stress tests model adverse rate scenarios — so investors can evaluate downside — without taking a view on probability. The actual rate path is the market’s to set, not Lendmire’s to predict.

When numbers in an article matter to a real-money decision, get a real quote with your actual scenario. Calculators are useful for orientation, not commitment.

Frequently asked questions

• How often is the methodology page updated?

  We review the full methodology quarterly. Individual data sources (FRED MORTGAGE30US, Census ACS, Tax Foundation, NAIC) refresh on their own native cadences — see the Data sources section for each source’s update frequency. The “Methodology last reviewed” date at the top reflects the last full review of this page.

• What if a Lendmire article shows a different number than this methodology predicts?

  This page is the source of truth. If you spot a conflict between an article and this methodology, email [email protected] and we will update the article. Note that auto-updating data (current rate, current cash flow figures) may differ from the original article numbers because the live values reflect today’s market, not the publication date.

• How can I verify the underlying data sources independently?

  Every data source is hyperlinked in the Data sources section above. FRED MORTGAGE30US, U.S. Census Bureau ACS, Tax Foundation state property tax studies, and NAIC homeowner’s insurance averages are all publicly available datasets. Click through to verify directly at the primary source.

• My actual quote shows a different rate than the methodology assumes. Why?

  The methodology models well-qualified DSCR scenarios (DSCR ≥ 1.00, credit 700+, 5-year PPP) at the MORTGAGE30US benchmark. Your actual quoted rate depends on credit score, DSCR ratio, prepayment penalty selection, property type, LTV, state restrictions, and wholesale lender-specific pricing. Get a personalized quote at lendmire.com/mortgage-quote-direct-2/ for your specific numbers.

• Is DSCR financing available in my state?

  Lendmire is licensed as a mortgage broker in 16 states and brokers DSCR loans in 40 states (DSCR products are business-purpose loans and many states allow them under different licensing structures). Specific state availability is confirmed during your quote conversation. Verify our active state licensing at NMLS ConsumerAccess.

• Why does the methodology use 30% down for the conventional comparison?

  At roughly 30% down on a non-owner-occupied investment property, conventional mortgage pricing typically reaches parity with DSCR pricing after accounting for loan-level pricing adjustments (LLPAs). This is the apples-to-apples comparison point — same effective rate, same property. At lower down payments, conventional investment property prices materially worse than DSCR. The exact LLPA stack varies by credit score, LTV tier, and property type.

• Why is this methodology page so detailed?

  Because investor lending is too consequential for opaque math. If you’re making a real-money decision based on a Lendmire article, you should be able to trace every number back to a documented assumption — the data source, the formula, the default, and the limit. That’s what this page is for. The methodology is documented publicly because we want it scrutinized.

How articles are produced

Every article on lendmire.com follows the same five-stage editorial process, regardless of whether the topic is a single state hub or a city-level market guide. Articles are published under the Lendmire Research byline — the analytical group within Lendmire LLC. Lendmire Research operates as an editorial group, not a single named author: articles are accountable to the firm, not to an individual. The decision reflects an editorial preference — investors making capital decisions deserve content that’s accountable to the firm, not anchored to a single author’s continued employment. Every article is the firm’s work and the firm’s responsibility.

1. Research

   For each article, Lendmire Research compiles a market brief from primary sources only — U.S. Census Bureau ACS data, FRED MORTGAGE30US weekly observations, Tax Foundation state property tax studies, NAIC homeowner’s insurance averages, HUD Fair Market Rent tables, and local employer and economic data from chamber-of-commerce and government sources. Secondary aggregators and commercial content sites are excluded; only primary sources qualify.

2. Drafting

   Articles are drafted against the research brief, not against a template. Each article is written to be specific to its market — so market-specific that swapping the city name out wouldn’t yield a coherent article. That uniqueness is by design. Lendmire Research deliberately varies analytical framing market by market: a city with deep STR research gets a different treatment than a workforce-rental city with strong wage data, and a coastal market with insurance complexity is structured differently than an interior city where the math is simpler. The research determines each article’s shape.

3. Compliance review

   Before publication, every article is reviewed against Lendmire’s compliance standards. The standards: no superlative rate or pricing language (which would violate TILA/UDAAP mortgage advertising rules), no competitor names (Lendmire is lender-neutral by policy), strict third-person Lendmire Research voice, and no specific interest-rate quotes (which only the actual quote process can provide accurately). These are the rules Lendmire articles are written under — not a corrective filter applied afterward.

4. Editorial standards

   Six editorial standards define what a publishable Lendmire article looks like: factual specificity (real numbers and named sources, not generalities); local relevance (the analysis is genuinely market-specific, not template content with a city name pasted in); expertise signals (citation depth, technical accuracy on DSCR mechanics); voice authenticity (the article reads like a practitioner wrote it, not a marketing department); widget integration (interactive tools support the analysis rather than sit beside it); and compliance neutrality (no superlative claims, no competitor names, no rate quotes). Every article is held to all six.

5. Publication & ongoing refresh

   Published articles include live-updating data layers. Mortgage rate figures and DSCR coverage math auto-refresh on every page load against the current FRED observation, so an article published 18 months ago displays today’s rate, not the rate from publication day. The narrative reflects publication-era market conditions; the live data reflects right-now. See Update frequency & architecture for the technical detail.

Editorial principles

Six principles every Lendmire Research article is held to: