# Landis Financial Model Rent-to-own platform that buys homes on behalf of credit/savings-constrained buyers, rents to them while coaching them to mortgage-readiness, then sells them the home at a pre-agreed price. - Canonical: https://finamodel.com/startups/landis - Excel download: https://finamodel.com/startup-models/landis.xlsx - Category: Fintech - Model type: SaaS ARR / Valuation - Funding round: Series A - Funding: $165M - Founded: 2021 - Geography: US - 11 states at time of deck (IN, OH, PA, MD, WV, KY, TN, NC, SC, GA, AL); plan to expand nationally [DECK, slide 9] - Customer: B2B ## About the company Landis is a rent-to-own platform that buys homes for credit- or savings-constrained buyers, rents the homes while coaching customers toward mortgage readiness, and later sells at a pre-agreed price. It is a housing-access product built on a property portfolio. Each customer journey combines a residential property acquisition, a rental period, financial coaching, and an eventual sale or alternative exit. That structure makes Landis capital intensive and exposes it to property values, financing costs, occupancy, and customer conversion. The model should track properties acquired, purchase price, financing, rent, carrying costs, coaching duration, purchase conversion, and sale premium by cohort. A property-level portfolio schedule is essential, including equity commitments, debt, appreciation or downside scenarios, and cash returned from realised exits. ## What's included - 5-year monthly revenue build with stage-appropriate growth assumptions - Full P&L, headcount plan, and operating-expense schedule - Cash-flow statement, runway, and burn-rate tracking - Valuation via exit multiple with a DCF cross-check - Returns analysis with MOIC and IRR - Unit economics including CAC, LTV, payback, and cohort retention ## Product & value proposition - Landis pre-approves aspiring homeowners who cannot yet qualify for a mortgage, buys the home the client selects, rents it to them, provides monthly coaching (credit, down payment, debt management) and sells it to them at a pre-determined price once they are mortgage-ready - Four-step flow: (1) Client pre-approval + home search → (2) Landis acquires property → (3) Client rents from Landis during coaching period → (4) Client buys from Landis - Minimum credit score requirement: 550+ - Target client: low-to-moderate income first-time homebuyers; median client income $44,000 - Partner agent network for deal sourcing: Keller Williams, Century 21, eXp, Coldwell Banker, Berkshire Hathaway HomeServices, RE/MAX, Howard Hanna, Allen Tate, Better Homes & Gardens, Brown Harris Stevens ## Market - US Households: 127M - Renting Households: 43M (34% of total) - Renting Households Who Want to Own: 32M (75% of renters want to own) - First-time homebuyers this year (active TAM): 1.6M households - Eligible for Landis Program (SAM): 4.8M households - Future eligible (broader TAM): 25.6M households - Avg. Revenue per segment and total Market Size: in deck - Headline TAM claim: "30 million households" ## Revenue model Landis has two intertwined revenue streams implied by the model: 1. **Rent spread / carry**: Landis buys the home, rents it to the client. Rental income > carrying costs (mortgage/financing, taxes, insurance, maintenance) during the coaching period. 2. **Sale premium / option spread**: Home is sold to client at a "pre-determined price". Implied appreciation or markup baked in at signing. - Sample property prices: $115,000 / $176,900 / $224,000 - affordable single-family homes in secondary markets - Revenue per transaction is in the market-size table - Client acquisition channel: partner real estate agent referrals (10 major brokerages listed) ## Traction & metrics - Operating in 11 states - Case study client: single mother, income, pre-qualification amount, credit score / down payment / DTI at beginning and end of program all - Client testimonials show successful conversions to homeownership - Clients include agent who purchased her own home through Landis - No revenue, cohort, or portfolio-size figures disclosed ## Unit economics - Implied inputs available: property purchase prices ($115K–$224K range); client median income $44K ## Competition / moat - Deck does not name direct competitors - Stated differentiators: - Proprietary client underwriting technology / algorithm that identifies each client's "most viable path to mortgage-readiness" - 550+ credit score floor (vs. higher requirements elsewhere) - "Central hub" of 10 major brokerage partners driving referrals - Social impact positioning (low-to-moderate income focus) differentiates from purely commercial rent-to-own players ## Team & funding ask / use of funds - Disclaimer references "Landis Properties Investors LLC, a Delaware LLC" as the investment vehicle and describes it as not yet closed on its first investment - suggests this is an early LP / seed vehicle raise, not a VC equity round. --- ## Recommended financial model - **Archetype + why**: Real estate fund / rent-to-own portfolio model - NOT a standard SaaS or 3-statement operating model. Landis is balance-sheet heavy: each property is an asset acquisition, held during a rental/coaching period, then sold. The vehicle is a real estate LP ("Landis Properties Investors LLC"). The model must track a property portfolio, not just an operating P&L. - Primary archetype: **Real estate fund / deal-by-deal waterfall** (acquisition cost → rental cash flows → exit/sale proceeds → investor return) - Secondary layer: **Operating company P&L** (coaching staff, tech, G&A) funded separately or via fee income - **Forecast horizon & granularity**: - Property-level: deal-by-deal with monthly cash flows during hold period (coaching period likely 6–24 months) - Portfolio roll-up: monthly for years 1–2, quarterly for years 3–5 - Total horizon: 5 years - **Key drivers & assumptions**: - Number of homes acquired per period - Average home purchase price: ~$170K - Gross rental yield on purchase price: ~8–10% annualized - Hold/coaching period per client: 12–18 months - Sale price vs. purchase price (option spread): - Financing cost / leverage:] - Vacancy / non-payment rate: - States / geographic expansion: 11 states current; national expansion - **Scenarios (Base / Bull / Bear - which variables flex)**: - Bear: lower conversion rate (50%), no home price appreciation, higher vacancy (10%), tighter financing - Base: 75% conversion, ~2–3% annual HPA, 5% vacancy, steady leverage - Bull: 90% conversion, 5%+ HPA, 2% vacancy, ability to recycle capital faster (shorter hold periods) - **Required sheets / outputs**: 1. `Assumptions` - all drivers in one place 2. `Deal Model` - single property template (acquisition → monthly rent income → operating costs → sale proceeds → IRR/equity multiple) 3. `Portfolio Roll-Up` - portfolio of N homes, staggered cohorts by acquisition month 4. `Fund P&L` - gross revenue (rent + sale), total costs, net income to the vehicle 5. `Operating Co P&L` - coaching/tech/G&A opex of Landis Technologies Inc. (separate from property vehicle) 6. `Returns / Waterfall` - LP/GP split, preferred return, carried interest (if fund structure) 7. `Cash Flow & Deployment` - capital deployment schedule, recycling of sale proceeds into new acquisitions 8. `Sensitivity` - IRR / equity multiple vs. hold period, conversion rate, HPA, leverage ## Frequently asked questions ### Is the Landis financial model free? Yes. The Landis model is a free Excel download with live formulas. ### Can I change the assumptions? Yes. The workbook is editable and its live formulas recalculate when assumptions change.