Persona logo
Persona Financial Model

Dev Tools Startup Financials (Free Excel Download)

Customizable identity verification infrastructure (API + no-code) for businesses across any use case

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About this model

Persona provides identity infrastructure through APIs and no-code tools for customised verification flows. Its modular signals cover address, adverse media, business, email, phone, social, PEP, and watchlist data, supporting onboarding, KYC and AML, fraud prevention, authentication, underwriting, recovery, and high-risk transactions.

The commercial model is inferred to combine per-verification API consumption with platform fees for complex workflows. Persona sells to businesses across fintech, credit, education, hospitality, marketplaces, crypto, HR, digital pharmacy, and home viewing. The deck does not disclose check pricing, ARR, verification volume, or contract structure.

Founded in October 2018, Persona had more than 80 employees and named customers including Square, Brex, Coursera, AngelList, Udemy, BlockFi, Petal, Rently, Rippling, and Outdoorsy. BlockFi said conversion doubled after switching. The model should forecast customers, checks, mix, price, data costs, expansion, churn, compliance operations, and margin.

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 Persona

withpersona.com
Read the pitch deck
Persona pitch deck cover
View on makeslides.com
Total raised
$150.0M
Funding round
Series C
Founded
2021
Category
Dev Tools
Customer
B2B
Geography
US-headquartered

How to build a detailed financial model for Persona

A complete walkthrough of the business, drivers, and assumptions behind the downloadable Persona model - distilled from its pitch deck and publicly available information.

Product & value proposition

  • Trusted identity infrastructure that lets businesses build customized identity verification flows via API or no-code tools
  • Covers the full identity lifecycle: onboarding, KYC/AML, fraud prevention, high-risk transactions, authentication, privilege escalation, data governance, account recovery, underwriting
  • Modular "building blocks": data signals (Address Lookup, Adverse Media, Business Lookup, Email Risk, PEP List, Phone Number Risk, Social Media, Watchlists) assembled into customer-specific flows
  • Positioning: high flexibility AND high ease of implementation - beats single-point solutions (high ease, low flexibility), all-in-one solutions (moderate on both), and in-house solutions (high flexibility, low ease)
  • Identity framed as a relationship, not a transaction - implying ongoing/recurring verification logic rather than one-shot checks

Revenue model

Not explicitly stated in deck. Implied model:

  • API-based consumption (per-verification call) and/or SaaS platform subscription - typical for identity infrastructure companies
  • Sold direct to business customers (B2B); customer logos span Fintech, Credit, EdTech, Hospitality, Marketplace, Crypto, HR, Digital Pharmacy, Home Viewing verticals
  • No pricing tiers, per-check rates, or MRR/ARR figures are disclosed

Traction & metrics

  • Founded: October 2018
  • Employees: 80+
  • Named customers (slide 10): Square, Brex, SimpleHealth, Sonder, Coursera, AngelList, Udemy, BlockFi, Petal, Rently, Rippling, Outdoorsy
  • Customer testimonials cite: conversion rate doubled after switching from competitor (BlockFi, Director of KYC/AML); "several hours a day" saved on operations (Sonder)
  • No revenue, ARR, growth rate, verification volume, or customer count figures disclosed

Competition / moat

  • Competitive frame: single-point solutions (e.g., Jumio, Onfido) vs. all-in-one solutions (e.g., Socure) vs. in-house builds - Persona claims top-right quadrant: most flexible AND easiest to implement
  • Moat signals: modularity/customizability, network effects implied by "online identity network" framing, and depth of data signal integrations
  • No explicit moat/IP/defensibility slide

Team & funding ask / use of funds

  • CEO: Rick Song (ex-Square)
  • CTO: Charles Yeh (ex-Dropbox)
  • COO: Christie Kim (ex-Coursera, LinkedIn)
  • Investors on record: Bond, Coatue, First Round Capital, Founders Fund, Index Ventures, Insight Partners, Meritech
  • No funding ask amount, round size, or use of funds slide present in this deck

Recommended financial model

  • Archetype + why: Usage-based / consumption SaaS. Revenue should be modeled as verifications (or API calls) × price per verification, potentially layered with a platform/seat fee. Identity infrastructure companies typically have a hybrid: monthly platform minimum + per-verification overage. This is the correct archetype because the product is infrastructure consumed at transaction volume - not a fixed per-seat license.
  • Forecast horizon & granularity: 5-year annual model with monthly detail for Year 1–2 (needed to model cohort ramp and cash burn credibly). Suggested: 2021–2026.
  • Key drivers & assumptions:
DriverValue
Headcount (start)80+
FoundedOct 2018
  • Scenarios (Base / Bull / Bear - which variables flex):
  • Base: 40% YoY customer growth, blended $0.35/verification, 70% gross margin, NRR 115%
  • Bull: 60% customer growth, price holds at $0.40, NRR 130% (enterprise volume ramp)
  • Bear: 25% customer growth, pricing pressure to $0.25 (competitive), NRR 105%, gross margin compresses to 60% on higher data-provider costs
  • Required sheets / outputs:
  1. Assumptions - all drivers in one place, color-coded inputs
  2. Customer cohort model - new logos by year, churn, expansion volume
  3. Revenue build - verifications × price, by customer segment (SMB / Mid-Market / Enterprise)
  4. P&L (IS) - revenue, COGS, gross profit, S&M, R&D, G&A, EBITDA, net income
  5. Headcount plan - tied to revenue milestones
  6. Cash flow & runway - burn rate, cash balance, implied next raise timing
  7. KPI dashboard - ARR, NRR, gross margin %, CAC payback (if data emerges), logo count
  8. Scenario toggle - Base / Bull / Bear switch

Frequently asked

Is the Persona financial model free?+

Yes. The Persona 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 Persona'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

Alex Tapio, ex-Deloitte financial modelling expert

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.

Every model here is one I’d actually use for a client, and I personally vet each one before it goes up.

I’m not an expert in every industry, but I’ve built enough models to know what belongs in one. And when something is completely foreign to me, I reach out to my network for experts to work on our models with us.

Having a template library on hand cuts a first build from hours to minutes.

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