# ComplyAdvantage Financial Model AI-powered AML compliance SaaS platform providing real-time financial crime data (sanctions, PEPs, adverse media) and transaction monitoring/screening to banks and fintechs via API. - Canonical: https://finamodel.com/startups/complyadvantage - Excel download: https://finamodel.com/startup-models/complyadvantage.xlsx - Category: Fintech - Model type: SaaS ARR / Valuation - Funding round: Series C - Funding: $50M - Founded: 2021 - Geography: Global; UK-headquartered (Sunday Times Tech Track 100; Deloitte UK Fast 50) [DECK slide 16]. - Customer: B2B2C ## About the company ComplyAdvantage provides AI-powered financial-crime compliance software, including sanctions, PEP, adverse-media data, screening, and transaction monitoring. Banks and fintechs use its API and workflow tools to manage AML obligations with more current data. The product combines a recurring platform relationship with usage that can rise as a customer screens more entities or transactions. Implementation support may add one-time revenue, but the core commercial value comes from embedded compliance infrastructure and recurring data access. The model should build subscription ARR from new logos, licence tiers, expansion, and churn, then layer in volume-based pricing for screened entities or transactions. Implementation fees and delivery cost should be separated from recurring revenue to preserve a clear view of SaaS retention and gross margin. ## 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 core data products delivered via RESTful API: 1. **Global Sanctions & Watchlists** - 1,000s of government/regulatory/law-enforcement watchlists; sanction updates in 15 minutes, 7 hours ahead of official source emails. 2. **Politically Exposed Persons (PEPs)** - 100% of profiles checked for updates daily; consolidated with sanctions and adverse media. 3. **Adverse Media** - 10,000 unique qualified media sources analysed daily; 200M articles read/month; 150,000 profiles added monthly; 40,000 existing profiles updated daily; 3M adverse media individuals; 200+ countries covered. Platform modules: - Customer Screening & Monitoring (KYC/AML onboarding) - Transaction Screening & Monitoring (real-time and batch) - FinCrime Knowledge Graph (proprietary AI/ML-powered dataset) - Case Management, Analytics, Reporting Key differentiators: real-time updates (not nightly batches), API-first ("integrate in an afternoon"), ISO 27001 certified, configurable rule-based approach. ## Market - $2 trillion estimated to be laundered globally each year. - Record fines issued annually (no specific figure cited). - No TAM/SAM/SOM breakdown presented in deck. ## Revenue model Not explicitly stated in deck. Implied model based on product architecture: - **API subscription / SaaS licence**: customers integrate via RESTful API; pricing likely per-seat, per-entity-screened, or flat annual subscription tiered by volume. - **Platform licence**: transaction monitoring and case management modules are configurable platform tools - likely an additional recurring licence layer. - **Professional services**: dedicated implementation team mentioned - likely a one-time implementation fee or time-and-materials. No pricing tiers, ACV, or contract terms disclosed in deck. ## Traction & metrics Customer outcomes (no company-level revenue or customer count disclosed): - Large Global Retail Bank: reduced customer onboarding time by 50% via automated adverse media screening. - Large Global FinTech: reduced false positive rate by 74% while increasing ability to spot risks. - Santander (Corporate & Commercial Banking): reduced account application-to-open cycle time from 12 days to 2 days; 80% reduction in employee effort. - Platform scale example: 9,095,750 accepted transactions; 45,156 awaiting analysis; 642 escalated & accepted; 435 escalated; 115 escalated and blocked; 5 blocked - shown in a live UI screenshot. - Transaction monitoring product claims 60% reduction in alerts for customers. Awards / external validation (proxy for growth stage): - Sunday Times Tech Track 100: 16th fastest-growing private technology company in Britain. - Deloitte UK Technology Fast 50 (2019): 21st. - Celent Model Bank Award 2019: Commercial Customer Onboarding. - Finovate Awards: Best RegTech Solution 2019. - Financial Innovation Awards: Best Innovation in Product/Service Design for Corporate Digital Onboarding. No revenue figures, ARR, customer count, or growth rate disclosed in deck. ## Competition / moat Not directly addressed. Implied moats: - Proprietary FinCrime Knowledge Graph (AI/ML-powered, continuously updated). - Data freshness: sanctions updates in 15 minutes vs hours/days for legacy vendors. - Network effect on data: 200M articles/month processed; 40,000 profiles updated daily. - ISO 27001 certification. - Named competitors: not mentioned in deck. ## Team & funding ask / use of funds - CEO/Founder referenced only as "Charlie" (shortlisted for CityAM Entrepreneur of the Year). - No team slide, headcount, funding ask, raise amount, or use of funds in deck. --- ## Recommended financial model - **Archetype + why**: B2B SaaS ARR model with a usage/volume tier overlay. Revenue is recurring API subscription + platform licence; implementation fees are one-time. Standard SaaS ARR build is the right frame; add a volume-screened-entities driver to capture API consumption growth. - **Forecast horizon & granularity**: 3 years (Y1 monthly, Y2–Y3 quarterly). Monthly granularity in Y1 captures sales cycle ramp and implementation lag. - **Key drivers & assumptions**: - New logos signed per month - Average contract value (ACV) - Revenue mix: % from data subscription vs platform licence vs professional services - Implementation fee per new logo - Net Revenue Retention (NRR) - Gross churn rate - Gross margin - S&M as % of revenue - R&D as % of revenue - G&A as % of revenue - Headcount plan: sales reps, data engineers, compliance analysts - Implementation duration - **Scenarios (Base / Bull / Bear - which variables flex)**: - **Bear**: slower enterprise sales cycles, ACV pressure from fintechs, higher data infrastructure COGS, NRR ~110%. - **Base**: steady logo additions, blended ACV ~$100K, NRR ~118%, gross margin ~72%. - **Bull**: accelerated enterprise deals (Tier 1 banks at $200K+ ACV), cross-sell of all three modules, NRR ~130%. - Flex variables: new logos/month, ACV, NRR, gross margin. - **Required sheets / outputs**: 1. Assumptions dashboard (all drivers in one place) 2. ARR bridge (new ARR, expansion ARR, churned ARR, net new ARR) 3. Revenue P&L (subscription revenue + implementation fees) 4. Operating expense build (S&M, R&D, G&A, headcount) 5. EBITDA / cash burn timeline 6. Customer cohort table (logo count, ACV, NRR by cohort year) 7. Scenario toggle (Base / Bull / Bear) ## Frequently asked questions ### Is the ComplyAdvantage financial model free? Yes. The ComplyAdvantage 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.