TITiko Financial Model
PropTech Startup Financials (Free Excel Download)
Spanish proptech iBuyer / digital broker that buys residential properties instantly using an AI-driven AVM, then resells them
professionals from Deloitte
Used by professionals from
About this model
Tiko is a Spanish iBuyer and digital broker using an AI-driven automated valuation model to buy homes instantly and resell them. It offers homeowners speed and certainty, while taking inventory and pricing risk onto its own balance sheet.
The company operates in Madrid, Barcelona, Malaga, Seville, and Valencia, with Lisbon identified as the next market. Its model combines principal buy-to-sell economics with digital brokerage fees, so property volume and resale spreads must be separated.
The model forecasts homes acquired, purchase price, renovation, days held, sale price, brokerage transactions, and fee revenue. Financing, property losses, operating costs, contribution margin, and market-launch assumptions show the cash intensity and sensitivity of the iBuyer model.
A turnkey financial model
Live formulas, no hardcoded values
Outputs are driven by live formulas, so the workbook updates from its assumptions instead of relying on hardcoded results.
All assumptions in one tab
Inputs are clearly marked in the Assumptions tab and separated from calculations, making it clear what to change and what to leave intact.
Statements always balancing
For integrated-statement models, the balance sheet, cash flow, and supporting schedules tie through properly.
Distinct schedules for clarity
Debt, working capital, taxes, and cash flow can get messy quickly. We group calculations in clear schedules, not across disconnected tabs.
No hidden macros or external links
There are no unexplained external workbook links or macros to undermine auditability or portability.
Changes flow through the model
Update a key driver and see the impact carry through the forecast, financing, and return outputs. We never use hardcoded numbers in formulas.
About Tiko
tiko.com
How to build a detailed financial model for Tiko
A complete walkthrough of the business, drivers, and assumptions behind the downloadable Tiko model - distilled from its pitch deck and publicly available information.
Product & value proposition
- Proprietary Automated Valuation Model (TikoAnalytics™) processes 2.8M data points/day
- Two liquidity channels: (1) Digital Brokerage - qualifies properties for institutional fund buyers, earns brokerage commission; (2) Buy-to-Sell - Tiko buys direct, renovates lightly if needed, resells
- Fully digital process: online form → 24-hour offer → digital signing → close in a few days
- Seller gets a cash offer at ~8% discount to fair market value
- Technology efficiency: team of 40 vs. 110+ at comparable-volume competitors; Opendoor has 1,600 staff
Market
- Described as "Europe's biggest asset class - one of the least liquid and least digitised"
- No TAM/SAM/SOM figures provided in deck
- Spain-specific supply context: 22% of all Madrid residential properties listed reach Tiko; up to 25% in other cities
- Commitment to deliver 5,000 properties to institutional fund buyers over 3–5 years (digital brokerage channel)
Revenue model
Two channels:
Channel 1 - Digital Brokerage (capital-light)
- Tiko qualifies and inspects properties, passes to institutional fund buyers
- Revenue = brokerage commission on transaction value
- Stated as 40% of business in 2021
- Commission rate not disclosed
Channel 2 - Buy-to-Sell (capital-intensive, principal)
- Tiko acquires property at ~8% discount to AVM, renovates minimally, resells
- Revenue = gross spread on resale; gross margin 8.4%, net margin 2.3% (€5k/property)
- Average hold: 86 days total (58 days on market)
Future / ancillary revenue (flagged but not sized):
- Built-in financial products
- Add-on sales (insurance, utilities, relocation)
- Lead resale to real-estate agents
Traction & metrics
Transaction volume (Annual Total Transaction Volume):
- 2018: €6.9M
- 2019: €21.3M
- 2020: €39M
- 2021F: €98M
- 2022 Outlook: €250M
Lead volume (quarterly):
- Q4 2019: 3,065 leads (YoY +151%)
- Q1 2020: 7,955 leads (YoY +175%)
- Q2 2020: 5,175 leads (YoY +99%; COVID dip)
- Q3 2020: 8,076 leads (YoY +133%)
- Q4 2020: 7,706 leads (YoY +151%)
Market share: 22% of Madrid residential supply; up to 25% in other cities Lead capture: 75% of all leads come to Tiko first; 51% come only to Tiko NPS: ~70 Total funding secured: €90M debt + equity Investors: btov, Rocket Internet / Global Founders Capital, Cabiedes Partners, TA Ventures
Unit economics
| Line | % of property value | Notes |
|---|---|---|
| Gross margin | +8.4% | ~€18,600 on avg property |
| Official costs (ITP + Notary + Registry) | 2.3% | Varies by city |
| Marketing | 1.5% | - |
| Renovation | 0.3% | - |
| Cost of capital | 2.1% | - |
| Net margin | +2.3% | ~€5,000/property |
- IRR: 35%
- Days on market: 58; total days: 86
- Historical gross margin consistency: 9.8% in 2018, 9.8% in 2019
- Historical IRR: 55.1% (2018), 51.6% (2019) - declined to 35% in 2021 YTD
- Historical avg holding days: 65.1 (2018), 69.3 (2019); 86 in 2021
- Implied avg property value: ~€221k (€18,600 / 8.4%)
Competition / moat
- Opendoor (US): iBuying only, 1,600 staff, similar digitisation but no capital-light brokerage channel
- Other European "iBuyers": iBuying only, larger teams (150+), less automated AVM
- Tiko moat: (1) dual-channel model reduces capital intensity vs. pure iBuyers; (2) proprietary TikoAnalytics™ AVM with city-specific ML/GIS; (3) first-mover in Spain with 22%+ market share in Madrid; (4) lean opex (40 staff); (5) high NPS / word-of-mouth flywheel
Team & funding ask / use of funds
Team: 40+ people
- Sina Afra - Founder & CEO; prior: Markafoni (exit), ex-eBay; Harvard Business School
- Ana Villanueva - Co-founder & CEO Iberia; ex-Booz & Company, ex-Arthur D. Little; MIT Sloan
- Can Gunay - Co-founder & VP Technology; founder of La Redoute; angel investor
- Paco Sahuquillo - Co-founder & COO Iberia; ex-consultant; INSEAD
Total funding to date: €90M debt + equity This raise: Series A (amount not specified)
Use of funds (4 areas):
- Further develop TikoAnalytics™ (integrate seller data, lower error rates, digitalise public data)
- Leverage capital structure (secure additional debt for buy-to-sell channel)
- Launch marketing levers (automation, PR, brand-building)
- Expand to Lisbon + up to 2 more Spanish cities
Recommended financial model
Archetype + why: Dual-channel proptech operating model - a hybrid of:
- Buy-to-Sell inventory P&L (principal capital deployment, gross spread, inventory turnover, cost of capital) for Channel 2
- Transaction fee / brokerage revenue model for Channel 1
This is NOT a SaaS or marketplace GMV model. The buy-to-sell channel resembles a real-estate inventory business (acquire → hold → resell) with a working capital cycle of ~86 days. The brokerage channel is asset-light fee income. Both channels are volume-driven.
Forecast horizon & granularity:
- 5-year annual model (2021–2026), with quarterly detail for years 1–2 (working capital cycle is material)
- Monthly cash / debt draw is important for buy-to-sell (86-day hold, debt-financed)
Key drivers & assumptions:
*Volume drivers:*
- Lead volume per quarter - Q4 2020: 7,706; forecast growth rate post-marketing ramp
- Lead-to-offer conversion rate
- Offer acceptance rate
- Channel split: Digital Brokerage vs. Buy-to-Sell
*Buy-to-Sell unit economics:*
- Avg property value: ~€221k
- Gross margin: 8.4%; held at 9.8% in 2018–2019 → model as ~8.5–9.5% base
- Official costs: 2.3%; fixed % of property value
- Marketing cost per unit: 1.5%
- Renovation cost: 0.3%
- Cost of capital: 2.1%; linked to debt rate and holding days
- Net margin: 2.3% (~€5k/unit)
- IRR: 35%
- Avg hold (total): 86 days → ~3 inventory turns/year
*Brokerage unit economics:*
- Brokerage commission rate
- Properties delivered to fund per year
*Operating expenses:*
- Headcount: 40 current; scale assumption
- Opex per transaction
*Capital / balance sheet:*
- Debt facility: existing €90M; additional to be raised
- Debt cost / interest rate
- Inventory balance = avg properties held × avg property value × hold days/365
- Equity: Series A proceeds (amount to be confirmed)
*Geographic expansion:*
- Lisbon + 2 Spanish cities -
Scenarios (Base / Bull / Bear - variables that flex):
- Lead volume growth rate (marketing ramp speed)
- Acceptance / conversion rates
- Avg property value (market conditions)
- Gross margin / spread (AVM accuracy, market competition)
- Channel mix (brokerage % vs. buy-to-sell %)
- Debt cost and availability
- Expansion pace (number of new cities / timing)
Required sheets / outputs:
- Assumptions - all drivers, clearly tagged; scenario toggle (Base/Bull/Bear)
- Lead Funnel - leads → offers → accepted → closed (by channel, by quarter)
- Buy-to-Sell P&L - unit economics waterfall × transaction volume; inventory turnover
- Brokerage Revenue - commission × volume
- Ancillary Revenue (optional stub for future monetisation)
- Operating Expenses - headcount + fixed/variable opex
- Debt / Working Capital Schedule - revolving facility draws tied to inventory balance; interest expense
- P&L Summary - consolidated revenue, gross profit, EBITDA, net income
- Balance Sheet - inventory, receivables, debt, equity
- Cash Flow Statement - operating CF (inventory build/release), financing CF (debt draws/repayments, equity raise)
- KPI Dashboard - transaction volume (€), units closed by channel, gross margin %, net margin %, IRR, holding days, leads, NPS (optional)
Frequently asked
Is the Tiko financial model free?+
Yes. The Tiko model is a free Excel (.xlsx) download with live formulas. Sign up with your email and the workbook is yours to keep, review, and edit.
What's included in the model?+
A 5-year monthly forecast with P&L, cash flow and runway, valuation (exit multiple plus a DCF cross-check), MOIC/IRR returns, and unit economics, with live formulas throughout.
How was this model built?+
It was built from Tiko's pitch deck and publicly available information, then structured to investment-banking standards as a fully editable Excel model.
Can I change the assumptions?+
Yes. You can change assumptions and the live formulas will recalculate in the downloadable Excel model.
Have more financial modelling questions? Contact us
Created by ex-finance professionals
Hey, I’m Alex and I created Finamodel.
Over my years in the finance industry I kept building the same models over and over again. Same structure, same assumptions, different logo. So I started building frameworks to turn them into clean, reusable templates.
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