# Flyhomes Financial Model Fully integrated homebuying platform (brokerage + mortgage + closing) that lets buyers win with cash offers and trade-up financing - Canonical: https://finamodel.com/startups/flyhomes - Excel download: https://finamodel.com/startup-models/flyhomes.xlsx - Category: Fintech - Model type: SaaS ARR / Valuation - Funding round: Series C - Funding: $150M - Founded: 2021 - Geography: US - Pacific Northwest (Seattle, Portland), Northern California (SF Bay Area), Southern California (LA, San Diego), Northeast (Boston) [DECK sl.16] - Customer: B2B ## About the company Flyhomes is an integrated homebuying platform combining brokerage, mortgage, closing, cash-offer, and trade-up financing services. It helps buyers compete in competitive markets by using short-term financing to make offers with the certainty of cash. A single home transaction can generate brokerage commission, mortgage-origination, and title or closing revenue. The cash-offer and trade-up products also introduce meaningful balance-sheet exposure while creating a differentiated customer proposition. The model should begin with home transactions and average purchase price, then apply revenue waterfalls for brokerage, mortgage, and title. Bridge-loan balances, capital turnover, interest income, funding cost, and loss or resale risk need a dedicated schedule rather than being buried in operating revenue. ## 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 Three integrated pillars: **Fintech products** - Cash Offer: Flyhomes purchases the home with a proprietary short-term bridge loan; buyer closes in as few as 9 days, then replaces with a long-term mortgage - Trade Up: Buyer receives a Guaranteed Price for their existing home (Flyhomes buys it if unsold within 90 days); buyer can make a cash offer on the new home before selling **Seamless experience** - Horizontally integrated: dedicated Client Advisor + team of experts - Vertically integrated: brokerage + mortgage + closing under one roof **Tech-driven** - Mobile app for search, tours (including live video tours), underwriting, and agent communication - Proprietary dataset to build smarter offers Outcome vs. industry: - Time to buy: 1 month (Flyhomes) vs. 4.5 months (industry) - 4.5x faster - Offers to win: 2.2 (Flyhomes) vs. 8.5 (industry) - 4x win rate - Winning offer price: 97.6% of highest competing offer - "tens of thousands in savings per deal" ## Market - US GTV (TAM): $1.7T - Existing US homes sold annually: 5M - Real estate agents: 2M - 99% of market described as available for disruption - Structural tailwinds: 3.3M home shortage; low interest rates; 40% of homebuyers are Millennials - Market competitiveness intensifying: avg. days on market fell from 43 → 21 (2020→2021, -51%); avg. number of offers in Flyhomes markets rose from 3.7 → 5.6 (+51%) **SAM (current 4-region footprint)**: - Annual GTV in current markets: $10B - Revenue opportunity (current markets, at 5% market share): $500M SOM / share target: 5% future market share in current 4 regions ## Revenue model Deck does not break out fee rates or revenue line items explicitly. Implied revenue streams from the integrated model: - **Buyer's agent commission**: earned on each closed transaction (industry standard 2.5–3% of home price; Flyhomes earns this as the buyer's agent) - **Mortgage origination / spread**: Flyhomes originates the long-term mortgage that replaces the short-term bridge loan - **Title / closing fees**: Flyhomes operates a closing vertical - **Short-term bridge loan interest / fee**: proprietary loan product used for the Cash Offer and Trade Up products; duration ~9 days to close, then replaced - **Trade Up Guaranteed Price spread**: potential margin if Flyhomes must purchase the seller's existing home Revenue per transaction is therefore a bundle of multiple fee streams (brokerage + mortgage + title), which the deck frames as eliminating fragmented CAC across parties. Revenue opportunity target: $500M in current 4-region markets at 5% market share on $10B GTV - implies blended revenue take rate of ~5% of GTV. ## Traction & metrics - NPS: 78 (vs. lower scores for Traditional Agents, Mortgage, and Title) - ~600 five-star reviews on Zillow, Yelp, and Google - 10% of US employees were clients before joining - 36% of customers have made a referral - Time-to-close: 9 days with proprietary short-term loan - Offers to win: 2.2 average (vs. 8.5 industry) - On >50% of 2020 wins, Flyhomes won without the highest offer; avg. 2.4% below highest competing offer, in some cases up to 10% lower - Deck dated May 2021; market data cited as YTD May 2021 No revenue, GMV/GTV transacted, customer count, or growth rate figures are disclosed in the deck. ## Unit economics - Revenue opportunity per market at 5% share implies ~$500M / $10B GTV = ~5% blended take rate - CAC: described as declining via flywheel (referrals/repeat lower blended CAC at scale); no dollar figure given - 50%+ of agents industry-wide found via referral/repeat ## Competition / moat Competitive positioning: 2×2 matrix (buyer-focused vs. seller-focused; customer-centric vs. agent-centric) - Flyhomes: buyer-focused + customer-centric (sole occupant of that quadrant) - iBuyers (Opendoor, Offerpad, Zillow): seller-focused + customer-centric - Traditional brokerages (KW, RE/MAX, Compass, etc.): seller-focused + agent-centric - Discount brokerages (Redfin, REX, homie, etc.): seller-focused + customer-centric - Agent liquidity tools (Knock, HomeLight, Homeward, Ribbon): buyer-focused + agent-centric Stated moats: - Proprietary dataset → smarter offers (win without the highest bid) - Vertical integration → single P&L, no fragmented CAC across brokerage/mortgage/title - Referral flywheel → 36% referral rate; scale reduces paid CAC - Brand trust ("10% of employees were clients first") - Network effects from data accumulation ## Team & funding ask / use of funds **Team**: - Tushar Garg - CEO / Co-Founder - Ryan Dibble - COO / Founding Member - Adam Hopson - Strategy & Growth - Gaganpreet Luthra - Global Ops - Mark Lee - General Counsel - Meredith Han - Product - Rehan Mohammad - Finance & Biz Ops - Sam Kasle - Sales - Tracie Hlavka - Engineering - Prior employers: Amazon, McKinsey, Microsoft, LendingHome, LendingClub, Blue Nile, Brooks, JPMorgan, Fidelity, LinkedIn, Barclays, Porch, Pluralsight, Expedia **Board**: - Alex Rampell - a16z (TrialPay founder) - Lisa Wu - Norwest Venture Partners - Mark Vadon - Blue Nile, Zulily - Mike Ghaffary - Canvas Ventures (Yelp) - Stephen Lane - Co-Founder - Roger Lee - Battery Ventures --- ## Recommended financial model - **Archetype + why**: Multi-revenue-stream real estate brokerage / proptech operating model - specifically a **GTV-to-revenue waterfall** model with embedded fintech product P&Ls. The business has three linked revenue engines (brokerage commission, mortgage origination, title/closing fees) that all flow from a single transaction volume (GTV), plus a balance-sheet-intensive bridge lending book (Cash Offer / Trade Up). A pure SaaS ARR model is wrong; a marketplace GMV model is closer but misses the mortgage and bridge lending. Best framed as: GTV → blended take rate → gross revenue by product line → contribution margin by vertical → consolidated operating P&L, with a separate schedule for the bridge loan book (outstanding balance, duration, cost of funds, interest income/spread). - **Forecast horizon & granularity**: 5-year annual (2021–2025), with Year 1–2 in quarterly detail. Monthly is unnecessary given transaction-based (not subscription) revenue and multi-month close cycles. - **Key drivers & assumptions**: - **GTV per market** - current 4-region TAM = $10B annual GTV; starting penetration rate - **Market share ramp** - target 5% in current regions; - **Average home price per market** - - **Transactions per year** = GTV / avg home price - **Blended revenue take rate** - implied ~5% of GTV; broken into: buyer-side commission ~2.5–3%, mortgage origination ~0.5–1%, title/closing ~0.25–0.5% - **Cash Offer / Trade Up product mix** - ; drives balance sheet sizing - **Bridge loan book** - avg loan duration ~30 days; avg loan = avg home price; cost of funds - **Gross margin by vertical** - brokerage; mortgage; title - **CAC (paid)** - ; mix: 40% referral (zero cash CAC), 15% online, 21% traditional channels, 11% other, 13% repeat - **Headcount / agent model** - - **Market expansion** - deck shows 4 current regions; - **NPS / referral rate** - 36% referral rate; drives organic CAC reduction [modeled as blended CAC decline] - **Scenarios (Base / Bull / Bear - which variables flex)**: - **Base**: 5% market share in current 4 regions by Year 5; blended take rate ~5%; organic referral flywheel keeps blended CAC flat to declining - **Bull**: 5% market share achieved in Year 3; 2–3 new metros added in Years 3–4; take rate expands as mortgage penetration deepens; bridge loan book generates incremental spread income - **Bear**: Market share ramp slows to 2–3% by Year 5 (competition from iBuyers / Redfin intensifies); rising interest rates compress bridge loan economics and mortgage volume; CAC rises if referral flywheel underperforms; home price correction reduces GTV - **Required sheets / outputs**: 1. **Assumptions** - all drivers in one place, color-coded inputs 2. **Transaction Volume** - markets × share × avg price → annual/quarterly GTV and transaction count 3. **Revenue Waterfall** - GTV → commission revenue, mortgage revenue, title revenue, bridge loan interest income; total net revenue 4. **Bridge Loan Book** - avg outstanding balance, cost of funds, net interest spread, capital requirement 5. **P&L** - revenue by line, gross profit by vertical, S&M (CAC × transactions), tech/product opex, G&A, EBITDA 6. **Unit Economics Summary** - revenue per transaction, gross profit per transaction, CAC, LTV proxy (referral-adjusted), payback period 7. **Scenario toggle** - Base / Bull / Bear with sensitivity table (market share % × blended take rate → revenue; and home price × transactions → GTV) 8. **KPI Dashboard** - GTV, transactions, NPS (static), market share %, revenue, gross margin %, EBITDA, cash burn ## Frequently asked questions ### Is the Flyhomes financial model free? Yes. The Flyhomes 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.