# dLocal Financial Model B2B payments infrastructure enabling global merchants to accept and send payments via 300+ local payment methods across emerging markets. - Canonical: https://finamodel.com/startups/dlocal - Excel download: https://finamodel.com/startup-models/dlocal.xlsx - Category: Fintech - Model type: SaaS ARR / Valuation - Funding round: Growth - Funding: $200M - Founded: 2020 - Geography: 20 countries across Latin America, Africa, and Asia (current); targeting 15 additional markets [DECK, slide 6 & 9]. - Customer: B2B2C ## About the company dLocal provides payment infrastructure that lets global merchants accept and send money through more than 300 local payment methods in emerging markets. A single integration gives enterprise customers access to consumers who often do not use international cards. The company operates across Latin America, Africa, and Asia, serving global platforms that need both pay-in collection and pay-out capability. Local integrations, regulatory complexity, and enterprise merchant relationships form the operating foundation of the business. The model is TPV-led: forecast payment volume by merchant, market, and pay-in or pay-out product, then apply net take rates and FX economics. Revenue growth, processing cost, geographic expansion, and operating leverage should feed through to EBITDA and cash generation in a payments P&L. ## 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 - 360-degree payment platform connecting global merchants to emerging market consumers. - Two core use cases: - **Accept payments**: global merchants collect money from EM consumers using 300+ local methods. - **Pay vendors / disbursements**: merchants pay out to vendors and partners in local markets. - **Move money**: global financial institutions move funds in and out of emerging markets. - Single API integration for all markets and methods. - Key insight: 63% of EM consumers are unbanked; 90.5% have no credit card; international credit cards represent only 22% of EM payment mix. dLocal's value is routing volume through the 78% of non-card local methods that global PSPs cannot reach. ## Market - 2.3B emerging market consumers addressable. - eCommerce growth in emerging markets: +25%. Period not specified. - Payment mix in emerging markets: - Domestic credit cards: 34.0% - International credit cards: 22.0% - Others (mainly e-wallets): 20.0% - Cash payment: 12.0% - Bank transfers: 9.0% - Local debit cards: 3.0% - No explicit TAM/SAM/SOM dollar figures provided. ## Revenue model - Transaction-fee model: standard for payment processors - dLocal earns a percentage take-rate on Total Payment Volume (TPV) processed. No explicit take-rate or fee schedule disclosed in deck. - Two revenue streams implied: 1. **Pay-in fees**: merchants pay to collect from EM consumers. 2. **Pay-out fees**: merchants/FIs pay to disburse to EM recipients. - FX spread likely additional revenue source: cross-border EM transactions typically carry FX conversion margin. - Distribution: direct API integration with global enterprise merchants (Microsoft, Amazon, Google cited as clients). ## Traction & metrics - Revenue growth: "Double revenue every year". No base revenue figure disclosed. - Profitable since day 1. - Client penetration: 50% of the top 10 biggest global companies use the platform. Named clients: Microsoft, Amazon, Google. - Current footprint: 20 countries, 300+ local payment methods. - No GMV/TPV, ARR, customer count, or transaction volume figures disclosed. ## Competition / moat - Not explicitly addressed in deck. - Implicit moats visible from deck content: - 300+ local payment method integrations (high integration cost to replicate). - Regulatory/licensing complexity across 20 EM jurisdictions. - Enterprise client lock-in: Microsoft, Amazon, Google as named anchor clients. - Profitable from day 1 suggests efficient cost structure relative to competitors burning capital. ## Team & funding ask / use of funds - Funding ask / valuation: Not explicitly stated. - Use of funds implied by "dLocal's needs" slide: - Maintain profitability (no equity burn required for operations). - Scale: expand to 15 new markets. - Deepen value for existing merchant base ("connections"). - Nature of ask is ambiguous - could be equity raise, strategic partnership, or commercial BD pitch given the "Win in emerging markets with d·local" closing slide. ## Recommended financial model - **Archetype + why**: TPV-based payments P&L. dLocal is a payment processor; the correct model builds from Total Payment Volume → net revenue via take-rate → operating cost stack → EBITDA. This mirrors how Adyen, EBANX, and similar EM-focused processors are modeled. A 3-statement wrap is warranted given the profitability claim and investor context. - **Forecast horizon & granularity**: 5 years (Year 1–5), annual columns. Monthly detail for Year 1 if cash flow schedule needed, but given no burn the annual view is primary. - **Key drivers & assumptions**: - TPV base year: ~$500M–$1B range implied by enterprise client base (Microsoft, Amazon, Google) and 20-country footprint; no figure in deck - flag as critical open item. - TPV growth rate: ~100% YoY ("double revenue every year"); model tapering from 100% → 60% → 40% → 30% → 20% as law of large numbers kicks in. - Net take-rate (revenue / TPV): 1.0%–1.5%, consistent with EM processor peers (EBANX ~1.2%, Adyen net interchange ~0.3% but higher processing margin). - Pay-in vs pay-out revenue mix: 70% pay-in / 30% pay-out based on typical processor mix; flex as scenario variable. - FX spread contribution: modeled as 0.1%–0.2% of cross-border TPV; toggle on/off. - Gross margin: 50%–60% of net revenue after payment scheme fees, local bank costs, and regulatory charges; EM processors typically lower than pure-software peers. - Operating cost structure: headcount-heavy for compliance and local market ops; model as % of revenue scaling down from ~40% to ~25% over 5 years. - Country expansion: 15 new markets targeted; model adds 3–5 markets/year with 12-month ramp to meaningful TPV contribution; each new market carries ~$0.5M–$1M upfront licensing/integration cost. - EBITDA margin: Year 1 ~15%–20% (consistent with "profitable from day 1"); scaling toward 30%+ by Year 5. - Capex / infrastructure: low capex model (cloud-based API infrastructure); depreciation immaterial. - **Scenarios (Base / Bull / Bear)**: - Base: 100% → 60% → 40% → 30% → 20% TPV CAGR; take-rate holds at 1.2%; 15 new markets over 4 years. - Bull: TPV growth sustains at 100%+ for 2 more years; take-rate expands to 1.5% as FX/disbursement mix grows; all 15 markets in 2 years. - Bear: Growth decelerates to 50% in Year 1 (macro/FX headwinds in EM); take-rate compresses to 0.8% on competitive pressure; only 5–7 new markets achieved. - Key flex variables: TPV growth rate, net take-rate, new market count, gross margin. - **Required sheets / outputs**: 1. Assumptions dashboard (all drivers in one place, color-coded inputs). 2. TPV build (by region/country cohort, pay-in vs pay-out split). 3. Revenue bridge (TPV × take-rate → net revenue, FX spread add-on). 4. P&L (gross profit → EBITDA → EBIT → net income). 5. Operating cost detail (headcount, compliance, infrastructure, S&M). 6. Country expansion schedule (existing 20 + 15 new, ramp assumptions). 7. Scenario toggle (Base / Bull / Bear). 8. Summary KPI output (TPV, net revenue, gross margin %, EBITDA %, implied valuation at exit multiples). ## Frequently asked questions ### Is the dLocal financial model free? Yes. The dLocal 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.