NENeuro-ID Financial Model
InsurTech Startup Financials (Free Excel Download)
Behavioral analytics SaaS platform that translates "digital body language" into real-time fraud detection and friction reduction scores for digital onboarding.
professionals from Deloitte
Used by professionals from
About this model
Neuro-ID uses behavioral analytics to translate typing, tapping, scrolling, and other digital-body-language signals into fraud and friction scores. A lightweight script helps payments, lending, insurance, and fintech customers identify genuine users and riskier onboarding attempts.
The company monitors more than 92 million sessions and reports fraud reduction above 35% for customers. Its commercial model is enterprise subscription software with multi-year contracts and higher ACV on renewal.
The model is enterprise SaaS ARR. Customers, contract value, monitored sessions, expansion, renewals, and churn build revenue. Data processing cost, sales capacity, fraud-performance proof, and retention determine 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 Neuro-ID
How to build a detailed financial model for Neuro-ID
A complete walkthrough of the business, drivers, and assumptions behind the downloadable Neuro-ID model - distilled from its pitch deck and publicly available information.
Product & value proposition
- Captures digital body language signals (typing, mousing, tapping, scrolling) via a lightweight JavaScript snippet embedded in digital properties.
- Outputs: Friction Index® Dashboard, Neuro Attributes for Fraud, Neuro Confidence Scores (NCS), API.
- Dual value: (1) fast-track genuine applicants through low-friction journey; (2) flag fraudulent applicants for higher-friction verification.
- Use cases on genuine applicants: Fast Track, Friction Index optimization, drop-off prediction, drop-off reduction.
- Use cases on fraudulent applicants: low familiarity detection, session fluency, computer savviness, criminal behavior profiling.
- Two foundational patents held by academic co-founders.
Market
- TAM framing: "$1.3T Annual Digital Transformation Problem is Growing." - stated as problem size, not an addressable market breakdown.
- No SAM, SOM, or formal TAM/SAM/SOM split in deck.
- Market narrative: digital transformation has accelerated fraud and friction simultaneously; Neuro-ID positions at the intersection.
Revenue model
- Enterprise SaaS subscription model (inferred from "multi-year contracts & higher ACV" language).
- No pricing tiers, ACV ranges, or seat/usage-based pricing disclosed in deck.
- Channel: direct enterprise sales (implied by customer description: industry leaders in Payments, Lending, Fintech, Insurance).
- Contract structure: multi-year renewals at higher ACV noted as a positive indicator.
Traction & metrics
- 92M+ Sessions Monitored - tracked on a growth chart from June 2017 to June 2020; Y-axis runs 20M–100M; curve starts near zero in mid-2017 and reaches ~92M+ by June 2020.
- Reducing Fraud by 35%+ for customers.
- Customers: "Industry leaders in Payments, Lending, Fintech and Insurance" - no customer count or named logos disclosed.
- Large enterprise customers renewing for multi-year contracts at higher ACV - directional NRR signal only, no number.
- CEO Jack Alton: three consecutive liquidity events exceeding $500M (prior track record, not Neuro-ID revenue).
- Co-founders: 30,000+ academic citations in HCI.
Competition / moat
- Moat claimed: proprietary patented technology (two foundational patents); unique behavioral data source not available elsewhere.
- No competitive landscape slide or named competitors in deck.
- Positioning: "Category Leader: Digital Onboarding."
- Differentiator: behavioral signal layer is additive to existing AI/ML fraud models (not a replacement).
Team & funding ask / use of funds
- Jack Alton - CEO; go-to-market specialist for disruptive tech; 3 prior liquidity events >$500M.
- Joe Valacich, PhD - CSO; co-founder; doctoral professor; 30,000+ citations; HCI global leader.
- Jeff Jenkins, PhD - CTO; co-founder; doctoral professor; HCI global leader.
- Jon Fetveit - CFO, Head of Strategy.
- Courtney Laabs - COO, Head of Customer Success.
- Advisors: David Montague (Expedia e-commerce fraud/risk), Brad Pennington (CRO - NS8, Prosper), Brian Elkins (CTO - SmarterHQ), Dave Boyce (Forrester board; CSO - XANT), Forrest Hobbs (CRO - Telesign, Usermind, Cloudleaf), Kevin Moss (former CRO - SoFi; former EVP/CRO - Wells Fargo).
Recommended financial model
- Archetype + why: Enterprise SaaS ARR model. Revenue is subscription-based (multi-year contracts, expanding ACV), sold to a defined enterprise vertical set. Standard SaaS ARR build (new ARR, expansion ARR, churn, net revenue retention) is the right frame.
- Forecast horizon & granularity: 5-year annual model (2020–2025), with Year 1–2 monthly detail to capture ramp dynamics. Quarterly suffices for years 3–5.
- Key drivers & assumptions:
| Driver | Value / Source |
|---|---|
| Starting ARR (2020) | ~$1–3M; consistent with early enterprise stage, 92M sessions but no revenue disclosed - treat as placeholder pending DD |
| New logo adds per year | 5–15 new enterprise logos/year in early years; industry leaders implies low volume, high ACV |
| Average ACV (new) | $150K–$300K; typical for behavioral analytics middleware sold to enterprise fintechs |
| ACV expansion rate | 120–130% NRR; deck signals multi-year renewals at higher ACV with no churn signals |
| Gross churn rate | 5–10% annually; enterprise cohort, sticky integration (JS snippet embedded in production flows) |
| Gross margin | 70–80%; SaaS with lightweight infra (JS + real-time analytics API); no COGS detail in deck |
| Sessions growth | 92M+ sessions by June 2020; session volume is a usage/capacity metric, not directly tied to pricing |
| S&M as % of revenue | 40–60% in early years; direct enterprise sales motion with specialist reps |
| R&D as % of revenue | 25–35%; patented tech requires ongoing development |
| G&A as % of revenue | 10–15% |
| Fraud reduction delivered | 35%+ for customers - used as a sales proof point, not a financial driver directly |
| Pricing model | Annual subscription; likely per-application-session or flat enterprise license - no pricing detail in deck |
- Scenarios (Base / Bull / Bear - which variables flex):
- Base: 10 new logos/year, $200K average ACV, 120% NRR, 75% gross margin.
- Bull: 20 new logos/year (category leadership accelerates), $300K ACV, 130% NRR - driven by expansion into insurance/payments.
- Bear: 5 new logos/year, $150K ACV, 110% NRR - longer enterprise sales cycles, tighter fraud budgets.
- Required sheets / outputs:
- Assumptions dashboard (all drivers, toggle for scenarios)
- ARR bridge (beginning ARR → new → expansion → churn → ending ARR)
- P&L (Revenue, COGS → Gross Profit, S&M, R&D, G&A → EBITDA → Net Income)
- Headcount plan (by function: sales, CS, engineering, G&A)
- Cash & runway (burn rate, capital required)
- Session volume tracker (92M base; project forward as a secondary KPI alongside ARR)
- NRR / cohort analysis (logo cohorts by year; expansion vs. churn waterfall)
- KPI summary (ARR, NRR, logo count, ACV, CAC, LTV - CAC and LTV estimated from headcount/ACV assumptions)
Frequently asked
Is the Neuro-ID financial model free?+
Yes. The Neuro-ID 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 Neuro-ID'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
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