Embedded Payments Benchmarks & Industry Data
The single source of truth for every quantitative figure cited across the Embedded Payments Knowledge Hub. Updated quarterly. Cite this, not the chapters.
Last updated June 2026 (v4) · Updated quarterly · Jane Podbelskaya
Chapter 11 of the Embedded Payments guide
Charge Forward Insight
Two findings stand out from the May 2026 dataset arrivals. First, Rainforest confirms that payments leadership structure — specifically, whether the payments leader sits in the C-suite — is the strongest single predictor of take rate. Median take rate for platforms with a C-suite payments leader is 98 bps; with a non-C-suite dedicated leader, 83 bps; with no dedicated leader, 53 bps. That is a 45-bps spread (~$900K/year on $200M GMV) attributable purely to organizational structure. Second, UBS Q6.0 introduces a new figure that did not exist in Q5.0: software platforms’ share of US SMB acquiring REVENUE (not volume) is projected to grow from ~47% in 2025 to ~60% in 2030. Volume share is even higher (~70% in 2025 → ~84% in 2030). For vertical SaaS platforms still on the fence about whether to invest in payments leadership and operating-model maturity, both findings sharpen the calculus.
1. Public-company embedded payments metrics
Vertical SaaS public companies with material embedded payments businesses, plus selected private/unlisted comparables. Drawn from the most recent annual filings and earnings calls as of May 2026. Companies vary substantially in how they disclose payment revenue — see methodology notes (Section 16).
| Company | Vertical | FY / Period | Total Revenue | Pmt / Fintech Rev | % Total | Volume | Net Take Rate | YoY |
|---|---|---|---|---|---|---|---|---|
| Toast (TOST) | Restaurant Tech | FY2024 + Q4 2025 | $4,961M FY24 | $4,254M FinTech | ~85.8% | $159.1B GPV | ~50 bps core; ~48 bps Q4 2025 actual | ~26% |
| Bill.com (BILL) | SMB AP/AR | FY2025 (Jun 2025) | $1.5B | ~$1.03B tx fees | ~69% tx | $329.8B TPV | ~31 bps | +19% |
| ServiceTitan (TTAN) | Trades / Field Svc | FY2026 (Jan 2026) | $961M (+24%) | ~$240M Usage | ~25% | $82.1B GTV | ~29 bps current; 55+ potential | +23% |
| Lightspeed (LSPD) | Retail/Rest POS | FY2025 (Mar 2025) | $1,077M | ~$748M Tx | ~69.5% | ~$93–100B GTV | ~75 bps | ~17% |
| AppFolio (APPF) | Property Mgmt | FY2024 (Dec 2024) | $794M | ~$430–480M est. | ~54–60% | N/D rent vol. | N/D (~33% VAS growth) | ~33% VAS |
| Procore (PCOR) | Construction Mgmt | FY2024 (Dec 2024) | $1,152M | Minimal / pre-revenue | <1% | N/D | N/A | N/A |
| Weave (WEAV) | Healthcare Comms | FY2024 (Dec 2024) | $204M | ~$18–22M est. | ~9–11% | N/D | N/D | >20% |
| Xero (XRO.AX) | Accounting/SMB | FY2025 (Mar 2025) | NZD $2,103M (~$1.3B USD) | Not separately disclosed | Nascent | NZD $30B+ (Melio) | ~0.5% (Melio implied) | N/A |
| Mindbody/ABC | Fitness/Wellness | Private | N/D | ~20% of recurring | ~20% | N/D | ~2.99–3.60% gross | N/D |
| Wix (WIX) | Horizontal SaaS | FY2025 (Dec 2025) | ~$1.8B est. | Not broken out | N/D | Not disclosed | Not disclosed | N/A |
| Shopify (SHOP) | eCommerce / Retail | FY2024 (Dec 2024) | $8,877M | ~$7B Merchant Solutions | ~78% | $292B GMV | ~210 bps blended | ~20%+ |
| Block / Square (XYZ) | SMB / Retail | FY2024 (Dec 2024) | ~$23.9B incl. BTC | ~$6B Square GP | ~25% on GP | ~$237B GPV (Square) | ~60–80 bps Square est. | Moderate |
⚑ FLAG — Q1 2026 earnings Most public vertical-SaaS companies on this table will have filed Q1 2026 10-Qs in May 2026 (Toast, Shopify, AppFolio, Bill.com). For board-grade work, verify the most recent quarterly disclosure before publication. Next-refresh queue tracks these explicitly (Section 16).
2. Rainforest 2026 Vertical SaaS Embedded Payments Benchmarking Study
★ NEW IN Q2 2026 — Full study now available Previous Ch 11 versions cited the UBS Vertex-conference recap of selected Rainforest findings. The full independent study was released in May 2026 (Q1 2026 fielded) — the first non-vendor, non-recap benchmark dataset on embedded payments performance in vertical SaaS. Hundreds of platforms responded; performance is reported at 50/75/90 percentiles by maturity, leadership, vertical, payment volume, and tenure.
Survey design: ~Q1 2026 field period; ~9 named verticals (fitness & wellness, healthcare, field & home services, education, nonprofits, government, professional services + “other”); ARR <$10M to $100M+; annual payment volume <$10M to >$10B; payments programs <1 year to 5+ years in operation. 76% of respondents have direct payment-metrics access; 87% are primary or shared payments-strategy decision-makers. Sample skews to $10M–$50M ARR (51% of respondents).
2a. Headline market benchmarks (all platforms, all verticals)
| Benchmark | 50th percentile (median) | 75th percentile | 90th percentile |
|---|---|---|---|
| Attach rate (% of new customers who sign up for payments) | 63% | 78% | 93% |
| Adoption rate (% of all eligible customers signed up) | 48% | 63% | 78% |
| Active adoption rate (% of signed-up who actively transact) | 63% | 78% | 93% |
| Take rate (effective % fee on payment volume) | 0.83% | 0.98% | 1.13%+ |
| Percent of platform revenue from payments | 30% | 35% | 40%+ |
2b. Performance by maturity stage
Maturity stage is the strongest predictor of four of the five benchmarks in the Rainforest dataset (the fifth — take rate — is most strongly predicted by leadership structure, see 2c). Self-reported by respondents using standardized definitions; cross-validated against benchmark performance.
| Benchmark (median) | Emerging (8% of sample) | Scaling (76% of sample) | Optimized (16% of sample) |
|---|---|---|---|
| Attach rate | 33% | 63% | 93% |
| Adoption rate | 33% | 48% | 78% |
| Active adoption rate | 48% | 63% | 78% |
| Take rate | 0.53% | 0.98% | 0.98% |
| Percent revenue from payments | 10% | 30% | 35% |
2c. Take rate by payments leadership structure (the most cited finding)
| Payments leadership structure | Median take rate (bps) | Implication |
|---|---|---|
| C-suite-level payments leader (CRO, CPO, GM Payments) | 98 bps | Top quartile of vertical SaaS platforms |
| Non-C-suite dedicated payments leader | 83 bps | 15-bps deficit vs. C-suite leadership |
| No dedicated payments leader | 53 bps | 45-bps spread vs. top quartile = ~$900K/yr on $200M GMV |
Reinforcing finding: 100% of Optimized platforms have a dedicated payments leader; 63% of those leaders are in the C-suite. Adoption is everyone’s job, but take rate is the payments leader’s job — that is the operational structure that produces the take-rate premium.
2d. The adoption gap — and what does (and does not) drive adoption
78% of platforms in the Rainforest sample target an adoption rate of 71%+ over the next 12–24 months. Only 25% have reached that level today. 40% target 86%+; only 4% achieve it today. Most platforms sit 15–30 percentage points below their stated adoption target — the gap holds across verticals, ARR bands, and years in payments.
| Driver / barrier | % of platforms citing | What it means |
|---|---|---|
| Seamless integration with core software (top adoption DRIVER) | 90% | Adoption is won on product depth, not pricing |
| Real-time payments data powering core workflows | 77% view as critical or very important | Only 25% report reliable access to accurate real-time data — large gap |
| Integration complexity (top adoption BARRIER) | 31% | Product friction blocks adoption |
| Trust / comfort with existing solutions (inertia) | 26% | Merchant switching cost is real even when value is clear |
| Competitive pricing (cited as driver) | 21% | Price matters far less than integration |
| Price sensitivity (cited as barrier) | 13% | Reinforces that price is rarely the binding constraint |
Charge Forward Insight
The Rainforest finding that price is the primary barrier for only 13% of platforms — while seamless integration is cited as the top driver by 90% — has direct implications for sell-rate strategy (Chapter 6). Most platforms under-price embedded payments because they treat it as commodity infrastructure. The data says the merchants on the other side of those checkout flows don’t see it that way — they’re paying for the integration, not the rate. If you are sitting on a sell rate that hasn’t been repriced since you launched, the Rainforest data is your evidence for taking price. Pair that with the Toast 7-lever framework (Section 12) and the Charge Forward Payments Revenue Calculator to quantify the move.
2e. Take rate trajectory and processing model
• 60% of platforms reported take-rate INCREASES over the last two years. 1% reported a decrease. 39% reported no change. The “race to the bottom” narrative is empirically wrong in vertical SaaS.
• 82% of platforms operate as Managed PayFac / PayFac-as-a-Service. 10% are Registered PayFacs. The remaining 8% are on referral or other models.
• 95%+ of platforms support card-not-present and ACH. 81% support digital wallets. 62% support card-present. 4% support BNPL. 0% currently support crypto.
• Platforms supporting digital wallets show 63% median adoption vs. 48% for platforms that do not — a 15-point delta (likely a maturity proxy as much as a causal driver).
• Card + digital wallet = ~73% of volume across the sample; ACH = ~27%.
2f. Fintech expansion (beyond payments)
| Embedded fintech product | % of platforms offering | Note |
|---|---|---|
| Payments only (no other fintech) | 52% | Majority of vertical SaaS is single-product fintech |
| Embedded capital / lending | 37% | First and most common expansion (matches Ch 10 sequencing) |
| Embedded payroll | 27% | Tied with bill pay; high-stickiness product |
| Bill pay / accounts payable | 27% | Particularly relevant in B2B verticals |
3. UBS “The Question 6.0” — software-led acquiring share
★ NEW IN Q2 2026 — Q6.0 replaces Q5.0 as canonical UBS Global Research, Tim Chiodo et al., “The Question 6.0: A framework for sizing and analyzing the various swimlanes of the US merchant acquiring market” (May 4, 2026). Re-baselines the swimlane framework with 2025 actuals and extends the forecast to 2030. Replaces Q5.0 (April 2025) and Q3.0 (June 2023) as the canonical source. Pace of share gains DECELERATED vs. Q5.0 — “still enough revenue to go around.”
3a. US merchant acquiring revenue — Q6.0 build
| Metric | Q6.0 (May 2026) figure | Note vs. Q5.0 |
|---|---|---|
| Total US merchant acquiring net revenue (2025) | ~$37B | Up from ~$35B in Q5.0 (2024 estimate) |
| Total US acquiring volume (2025) | ~$13T | New disclosure |
| Industry blended net take rate (2025) | ~28 bps | New disclosure; excludes interchange and network fees |
| Net revenue 2030E (UBS projection) | ~$50B | ~6% CAGR from 2025; in line with industry volume growth |
| SMB share of US net acquiring revenue | ~70% | BCG estimates ~75%; McKinsey ~2/3rds; aligned |
| SMB share of US acquiring VOLUME | ~25–30% | SMBs drive disproportionate revenue, not volume |
| SMB net take rate (UBS 2025 estimate) | ~80 bps | Forecast +1 bps/yr through 2030 |
| Mid-market & Enterprise net take rate (2025) | ~10 bps | Forecast –0.2 bps/yr through 2030 |
| Take rate range — merchants <$250k annual | 80–140 bps | High-end where micro-merchant pricing applies |
| Take rate range — merchants $250k–$1M annual | 35–115 bps | Wide spread reflects vertical and operating-model mix |
| Take rate range — merchants $1M–$100M annual | 15–35 bps | Volume-driven compression |
3b. Software platforms’ share of US merchant acquiring (Q6.0 update)
| Metric | 2024 actual (Q5.0) | 2025 actual (Q6.0) | 2029 (Q5.0) | 2030 (Q6.0) |
|---|---|---|---|---|
| Software platforms (broad) — share of total US acquiring revenue | ~33% | ~35% | >45% | ~45% |
| Modern acquirers (narrow) — share of total US acquiring revenue | ~21% | See Q6.0 detail | ~33% | See Q6.0 detail |
| Software platform US SMB acquiring VOLUME share | ~69% | ~70% | ~86% | ~84% |
| Software platform US SMB acquiring REVENUE share | Not separately disclosed | ~47% | Not in Q5.0 | ~60% |
⚑ FLAG — Pace decelerated vs. Q5.0 Q5.0 assumed ~83% market share for the named modern + scaled incumbent acquirers in 2026 and ~90% by 2029. Q6.0 has moderated this trajectory, concluding “there is still enough revenue to go around” — the share-shift continues but at a more measured pace. This is meaningful for company-specific forecasts: aggregated company guidance numbers from named acquirers may still be too high if the market grows at the lower Q6.0 rate. The directional thesis (software-led distribution wins) is unchanged.
3c. UBS swimlane framework — four channels of US merchant acquiring
| Swimlane | Definition | Trajectory (Q6.0) |
|---|---|---|
| 1. Software platforms | Owned vertical & horizontal SaaS (Square, Toast, Shopify, Clover) + software-led distribution partners (ISOs, banks, etc.) | Fastest-growing; net revenue several turns above software partners and SMB direct acquirers |
| 2. Payments partners (PSPs) | Merchant acquirers / PSPs embedding payments into software (Stripe Connect, Adyen for Platforms, Global Payments Integrated, Worldpay for Platforms / Payrix) | Second-fastest; “preferred partners become the app-store for payments and more” |
| 3. SMB direct | Traditional payments distribution not tightly integrated to a POS or other software platform | Declining; share loss accelerating |
| 4. Enterprise merchants | Direct distribution to large enterprise merchants | Stable volumes; slight pricing pressure |
3d. McKinsey 2025 Merchant Acquiring Survey — the 90% finding
★ NEW IN Q2 2026 — Headline corroborating data point McKinsey 2025 Merchant Acquiring Survey, published in “Decoding ISV maturity: A global playbook for payments growth” (January 8, 2026), surveyed 1,500+ US SMEs (defined as <$10M annual revenue). 90% of US SMEs reported using an ISV as their primary POS / payments / business-management solution — UP FROM ~50% IN 2022. McKinsey’s 2025 work also implies a ~$27B US payments revenue opportunity from SMEs, of which ~60% flows through ISVs.
Triangulation: UBS Q6.0 puts software platforms (broad) at ~35% of TOTAL US acquiring revenue in 2025, and ~47% of SMB acquiring revenue. McKinsey’s finding (60% of SME payments revenue flowing through ISVs in 2025) sits in the same range and is corroborating, not contradicting. Both sources point to a structural shift that is well underway, not theoretical.
3e. Triangulating with BCG / Adyen
BCG and Adyen, “Moving Embedded Finance from Promise to Practice” (September 2025), report SaaS providers offering integrated payments at 36% of SME acquiring revenues in 2024, projected to expand to 45% by 2028. Closely aligned with UBS Q6.0’s 35% (2025) → 45% (2030) — the two figures bracket each other and triangulate the directional shift.
3f. Take rate by merchant size — the pyramid
| Merchant size (annual volume) | Net acquiring take rate range | Notes |
|---|---|---|
| <$250k | 80–140 bps | Micro-merchant pricing; certain higher-risk verticals can exceed 140 bps |
| $250k – $1M | 35–115 bps | Wide range reflects vertical mix and operating-model variability |
| $1M – $100M | 15–35 bps | Mid-market; SMB / lower mid-market with negotiating leverage |
| $100M+ | LSD–LDD bps | Enterprise; top 5 US merchants ~LSD bps; remaining mid-market & enterprise ~12 bps |
4. Stripe 2025 annual letter — scale and trajectory
Per Stripe’s 2025 annual letter (released February 2026), recapped in UBS Global Research “Fast Take: Stripe Annual Letter” (February 24, 2026). Stripe is the largest single private platform-payments operator and a structural reference point for ecosystem scale.
| Metric | 2025 Actual | YoY Change | Notes |
|---|---|---|---|
| Total payment volume | $1.9 trillion | +34% YoY | vs. +38% in 2024 — modest deceleration; Adyen processed ~$1.6T ex-Cash App growing 20% in 2025 |
| New customer cohort growth (2025 vs. 2024 cohorts) | ~50% faster | — | New 2025 cohort signed up 50% faster than 2024 cohort |
| Geographic mix of 2025 cohort | ~57% non-US | — | Stripe is no longer primarily a US-centric platform |
| Stripe Capital funding volume | Disclosed | +45% YoY | Material lending volume growth |
| Revenue Recognition Suite run rate | On track to $1B in 2026 | — | Standalone product line approaching $1B annual revenue run rate |
5. UBS Visa & Mastercard adjusted US volumes vs. addressable PCE
Per UBS Global Research, “Visa & Mastercard: Adjusted US Volumes vs. Addressable US PCE Analysis” (April 8, 2026). The single best dataset for understanding whether the addressable consumer-to-business card pie is expanding or contracting.
| Metric | Recent Trend | Implication |
|---|---|---|
| V & MA reported US volume growth | ~6–7% | Headline number used by most analysts |
| Visa Direct + Mastercard Move share of total V/MA US volumes | >20% (UBSe) | New flows substantially padding reported volume growth |
| V & MA adjusted US C2B volumes vs. addressable PCE (last 4 yrs) | Roughly in line | Adjusted card volumes have NOT outgrown addressable consumer spending since ~2021 |
| Pre-COVID spread (2017–2019) | ~200–600 bps above PCE | The spread that historically characterized “card eating cash” has closed for adjusted C2B |
| Visa Direct share of Visa total payments volume | ~8–9% (FY2025–2026E) | Contributes ~100–200 bps to payments volume growth |
Charge Forward Insight
The most underappreciated finding in payments research over the past 12 months: the C2B card pie is no longer expanding faster than consumer spending. The macro is share-shift, not pie-expansion. Q6.0 confirms and quantifies this — software-led distribution is taking ~$3B+ of incremental annual share through 2030 from “Others” (traditional payments distribution not tightly integrated to software). Platforms that delay the move to embedded payments past 2027 will find the share-shift window narrower than the consultants’ TAM slides suggest.
6. PayFac registration contraction
| Metric | Figure | Source / Context |
|---|---|---|
| North American ISV/SaaS share of all registered Visa PayFacs (Mar 2023) | 47% | Baseline pre-2024 |
| North American ISV/SaaS share of all registered Visa PayFacs (early 2024) | 43% | Net contraction of 4 percentage points over ~12 months |
| Annual attrition rate of registered PayFacs | ~6% | Platforms registering, running the numbers, exiting after operational burden exceeded economic benefit |
| Rainforest 2026 — share of vertical SaaS on Managed PayFac / PFaaS | 82% | First independent survey-based confirmation that PFaaS is the modal operating model |
| Rainforest 2026 — share of vertical SaaS as Registered PayFacs | 10% | Approximately 10% of platforms in the sample are full Registered PayFacs |
| Mastercard characterization of PFaaS | ”A fundamental shift in how payments are being distributed” | Mastercard / Cardstream PayFac-as-a-Service White Paper, February 2025 |
7. Charge Forward Embedded Payments Maturity Framework
The five-stage Charge Forward framework is the canonical structural model used across this guide. Available as a standalone download at chargeforward.io/resources. The benchmarks below are the take-rate, annual revenue, and team profile we observe at each stage in advisory engagements.
| Stage | GMV Band | Net Take Rate | Annual Pmt Revenue | Margin | Team Evolution |
|---|---|---|---|---|---|
| 1 — Capability | $0–$50M | 10–35 bps | $0–$175K | 90%+ | Product Manager (part-time) |
| 2 — PFaaS Transition | $50M–$250M | 40–65 bps | $200K–$1.6M | 70–80% | Payments Manager |
| 3 — Margin Expansion | $250M–$500M | 65–80 bps | $1.6M–$4M | 60–75% | Head of Payments (small team) |
| 4 — Orchestration | $500M–$1B | 75–90 bps | $4M–$9M | 50–65% | Head of Fintech (small team) |
| 5 — Fintech | $1B+ | 90–120+ bps | $9M+ | Varies | Full Compliance Department |
Charge Forward Insight
The Charge Forward five-stage Maturity Framework (Capability / PFaaS Transition / Margin Expansion / Orchestration / Fintech) and the Rainforest three-stage maturity classification (Emerging / Scaling / Optimized) are complementary, not competing. CF Stage 1 (Capability) roughly maps to Rainforest Emerging. CF Stages 2–3 (PFaaS Transition + Margin Expansion) map to Rainforest Scaling. CF Stages 4–5 (Orchestration + Fintech) map to Rainforest Optimized. Use Rainforest stages for benchmarking against peers (what does median attach/adoption/take rate look like at your stage?) and CF stages for sequencing operational moves (what should I work on next?). The two are designed to be used together.
8. Net take-rate benchmarks by model and GMV
Net take rate is the platform’s retained economics after interchange, network fees, and processor costs. The table maps GMV tiers to the recommended embedded-payments model and the typical take-rate range observed in market.
| GMV Range | Recommended Model | Net Take Rate Range | Key Providers |
|---|---|---|---|
| <$10M | PSP Referral / Revenue Share | 0–20 bps | Stripe Connect Standard, Square Referral, Paysafe ISV, PayPal |
| $10–$50M | Light PFaaS / Revenue-Share Integration | 20–40 bps | NMI, Stripe Connect Custom, WePay/Chase, Adyen Lite |
| $50–$250M | Full PFaaS / Managed PayFac | 40–80 bps | Rainforest, Tilled, Finix, Payabli, Forward, Infinicept Launchpay |
| $250M–$1B | Managed PayFac + Orchestration | 65–90 bps | Worldpay/Payrix Pro, Adyen for Platforms, Finix mid-market |
| $1B+ | Full Registered PayFac (optional) | 100–120+ bps | Adyen for Platforms (enterprise), Stripe (custom), Finix Open, Infinicept |
Revenue potential by GMV tier
| Annual GMV | Model | Est. Net Take Rate | Est. Annual Net Pmt Revenue |
|---|---|---|---|
| $10M | PSP Referral | 10–20 bps | $10K–$20K |
| $25M | Light PFaaS | 25–35 bps | $63K–$88K |
| $50M | Full PFaaS | 50–70 bps | $250K–$350K |
| $100M | Full PFaaS | 60–80 bps | $600K–$800K |
| $250M | Managed PayFac | 70–85 bps | $1.75M–$2.1M |
| $500M | Managed PayFac | 75–90 bps | $3.75M–$4.5M |
| $1B+ | Full / Managed PayFac | 100–120 bps | $10M–$12M+ |
9. Average transaction value (ATV) by vertical
ATV drives interchange costs (higher ATV → higher absolute interchange per transaction), chargeback dollar exposure, and instrument choice (high-ATV B2B verticals push toward ACH).
| Vertical | Low ATV | Mid ATV | High ATV | CP / CNP Mix |
|---|---|---|---|---|
| Restaurants — QSR | $8 | $12–$15 | $20 | CP ~65–75% / CNP ~25–35% |
| Restaurants — Full-Service | $35 | $50–$65 | $100+ | CP ~60–70% / CNP ~30–40% |
| Property Management (Rent) | $800 | $1,100–$1,302 | $2,104 | CNP ~90–95% (ACH dominant) |
| Auto Repair (Dealerships) | $350 | $750–$1,130 | $3,000+ | CP ~70% / CNP ~30% |
| Healthcare / Dental (Patient Copay) | $50 | $150–$283 | $750+ | CP ~45–55% / CNP ~45–55% |
| Field Services — HVAC | $175 | $320–$650 | $5,500 install | CP ~48–52% / CNP ~48–52% |
| Field Services — Plumbing | $150 | $315–$500 | $856 | CP ~75% / CNP ~25% |
| Field Services — Electrical | $200 | $350–$600 | $2,000+ | CP ~75% / CNP ~25% |
| Fitness (Gym / Studio) | $10 | $38–$69 | $150+ | CNP ~75–85% / CP ~15–25% |
| Legal (Client Invoice) | $200 | $500–$2,000 | $10,000+ | CNP ~85–95% |
| Construction (Subcontractor) | $5,000 | $25,000–$75,000 | $500,000+ | CNP ~95%+ (ACH/wire dominant) |
10. Payment attach-rate benchmarks by vertical and stage
Attach rate = percentage of a platform’s active customers/locations processing payments through the embedded offering rather than a third-party processor. The single most important operational metric for payment revenue growth.
10a. Vertical-specific attach-rate ranges
| Vertical | Typical Attach Rate | Leader Attach Rate | Notes |
|---|---|---|---|
| Restaurant Tech | 55–65% | 75–85%+ (Toast est.) | Deep POS workflow integration; card near-universal |
| Property Management | 55–65% | 70–80%+ (AppFolio) | ACH dominates at ~90–95% of transactions |
| Fitness / Wellness | 45–55% | 65–75%+ (Mindbody) | Recurring stored-card CNP; elevated chargeback risk |
| Field Services / HVAC | 40–50% | 55–65%+ (ServiceTitan) | Mobile field payments; ServiceTitan ~50% per FY2026 mgmt |
| Auto Repair | 35–55% | 70%+ | ~70% CP mix; CNP growing for fleet/invoicing |
| Healthcare / Dental | 35–50% | 50–65%+ | Patient billing portals; mixed CP/CNP |
| Legal | 20–35% | 35–50%+ | High ATV ($500–$2,000+); ACH preferred for large matters |
| Construction | 25–40% | 40–55%+ | Lowest-attach vertical; ACH/wire dominant |
| Retail / POS | 40–55% | 60–75%+ (Lightspeed) | Lightspeed GPV/GTV: 37–38% (Q3 FY2026) |
10b. Attach + adoption by maturity stage (Rainforest 2026 — new in v4)
The Rainforest 2026 data set provides the first non-vendor benchmarks for attach and adoption stratified by maturity stage. Use these to identify your performance position regardless of vertical:
| Maturity stage | Median Attach Rate | Median Adoption Rate | Median Active Adoption Rate |
|---|---|---|---|
| Emerging (8% of sample) | 33% | 33% | 48% |
| Scaling (76% of sample) | 63% | 48% | 63% |
| Optimized (16% of sample) | 93% | 78% | 78% |
11. Interchange reference rates (US)
Interchange is a transfer fee from the merchant’s acquirer to the cardholder’s issuing bank. Visa and Mastercard set rates but do not receive them — network revenue comes primarily from assessment fees (Section 18b). Rates are published semiannually (typically April and October). The tables below reflect commonly-encountered US rates as of October 2025 (Visa) and April 2025 (Mastercard). See Chapter 5 for detailed mechanics.
11a. Visa US — selected rates
| Card Type | Card Category | CP Rate | CNP Rate |
|---|---|---|---|
| Consumer Credit | Standard (retail, low tier) | 1.18% + $0.05 | 3.15% + $0.10 |
| Consumer Debit | Unregulated / Exempt | 0.80% + $0.15 | 1.65% + $0.15 |
| Consumer Debit | Regulated (Durbin) | 0.05% + $0.21 | 0.05% + $0.21 |
| Commercial / Bus Credit | Corporate & Purchasing | 2.50% + $0.10 | 2.70% + $0.10 |
| Commercial / Bus Debit | Business Debit | 1.70% + $0.10 | 2.45% + $0.10 |
| Consumer Prepaid | Unregulated | 1.15% + $0.15 | 1.75% + $0.20 |
| Consumer Prepaid | Regulated (Durbin) | 0.05% + $0.21 | 0.05% + $0.21 |
11b. Mastercard US — selected rates
| Card Type | Card Category | CP Rate | CNP Rate |
|---|---|---|---|
| Consumer Credit | Merit III Base | 1.65% + $0.10 | 3.15% + $0.10 |
| Consumer Credit | Small Ticket | 1.65% + $0.02 | 1.95% + $0.02 |
| Consumer Debit | Unregulated (Merit III) | 1.05% + $0.15 | 1.65% + $0.15 |
| Consumer Debit | Regulated (Durbin) | 0.05% + $0.21 | 0.05% + $0.21 |
| Consumer Debit | Regulated + fraud adj. | 0.05% + $0.22 | 0.05% + $0.22 |
| Consumer Prepaid | Unregulated Standard | 1.90% + $0.25 | 1.90% + $0.25 |
| Commercial | Large Ticket ($10K–$25K) | 1.20% + $0.00 | 1.20% + $0.00 |
⚑ FLAG — Visa/Mastercard merchant settlement Both networks announced an updated proposed settlement with the injunctive relief class of US merchants in late 2025. The proposal includes an approximately 10-bps credit interchange reduction across the blended Visa/Mastercard credit pool. Settlement subject to court approval (Mastercard expects late 2026 or early 2027). Monitor for finalization. Source: Visa and Mastercard 8-K filings, December 2025.
12. Toast 7-lever take-rate optimization framework
Per UBS Global Research, “Toast: FinTech Net Take Rate Analysis & Core Payments Framework” (December 17, 2025). The seven illustrative levers UBS identifies for take-rate upside, in aggregate suggesting ~HSD-to-high-teens bps of net take-rate upside by 2028E if all levers were fully realized.
| # | Lever | Mechanism |
|---|---|---|
| 1 | Surcharging adoption | Pass credit-card processing fees to customers; adoption growing among SMB merchants |
| 2 | MDL-1720 settlement effects | Visa/Mastercard antitrust settlement with US merchants — includes ~10-bps credit interchange reduction |
| 3 | Regulated debit interchange routing | Reg II / 2023 Fed amendment — route eligible debit transactions to less expensive networks |
| 4 | Debit routing optimization | Within-network routing to lower-cost authorization paths |
| 5 | Processor / network partner negotiations | Volume-based renegotiation as platform GMV scales |
| 6 | Targeted SaaS and payments back-book pricing | Small, deliberate price increases on existing merchant cohorts |
| 7 | Instant Deposit offering | Premium feature where merchants pay for accelerated payout — incremental take-rate contribution |
13. Chargeback rate benchmarks
Card network monitoring programs have hard thresholds. Visa’s VDMP standard threshold is 0.9% (100 disputes/month); Mastercard’s MDRP Excessive Chargeback Merchant (ECM) threshold starts at 1.0%. Exceeding these triggers monthly fines ($50–$100/chargeback) and ultimately card acceptance termination.
13a. Card network dispute monitoring thresholds
| Program | Stage | Chargeback Rate Threshold | Monthly Disputes | Consequences |
|---|---|---|---|---|
| Visa VDMP | Early Warning | 0.65% | 75/month | Notification; no fine |
| Visa VDMP | Standard | 0.90% | 100/month | Monthly fines begin |
| Visa VDMP | Excessive | 1.80% | 1,000/month | Higher fines; potential suspension |
| Mastercard MDRP | Excessive Chargeback Merchant (ECM) | 1.00%–1.49% | Not separated | Fines begin; issuer notification |
| Mastercard MDRP | High Excessive Chargeback Merchant (HECM) | 1.50%+ | Not separated | Enhanced fines; potential termination |
13b. Chargeback rates by vertical
| Vertical | Avg. Chargeback Rate | Risk Level | Key Drivers |
|---|---|---|---|
| Restaurants — QSR / In-Person | 0.01–0.12% | Very Low | Low ticket; in-person; immediate consumption |
| Full-Service Restaurants | ~0.15–0.25% | Low | Delivery dispute friction |
| Property Management | ~0.05–0.15% | Very Low | ACH dominant; tenant disputes unusual |
| Auto Repair | ~0.12–0.25% | Low–Moderate | Service quality disputes; fleet card “not authorized” |
| Healthcare / Dental | ~0.15–0.30% | Low–Moderate | Billing confusion; insurance mismatch |
| Field Services (HVAC/Plumbing) | ~0.10–0.20% | Low–Moderate | Service disputes; unauthorized stored-card charges |
| Legal Services | ~0.15–0.35% | Low–Moderate | Post-engagement fee disagreements |
| Fitness / Health & Wellness | 0.50–0.86% | Moderate–High | Recurring billing disputes; first-party misuse |
| Software / SaaS (general) | 0.50–0.66% | Moderate | Recurring billing; forgotten subscriptions |
| Education & Training | 0.80–1.02% | High | Refund disputes; near-threshold risk |
| Travel & Hospitality | 0.89–1.65% | Very High | Cancellations; CNP-heavy; booking fraud |
| eCommerce / Digital Goods | 0.95–1.85% | Very High | CNP fraud; friendly fraud |
14. Valuation benchmarks
14a. William Blair — embedded finance valuation premium (September 2025)
| Platform Type | EV / Revenue | EV / EBITDA | Premium vs. Software-Only | GRR / NRR |
|---|---|---|---|---|
| Software-Only Platforms | 8.4x | 23.2x | Baseline | 93% / 105% |
| Software + Payments Platforms | 9.7x | 25.6x | +15–17% on EV/Revenue | ~95% / ~108% est. |
| Multi-product Embedded Finance Platforms | 12.7x | 28.1x | +51% on EV/Revenue | ~97%+ / ~111%+ est. |
14b. Windsor Drake — Vertical SaaS Valuation Report (Q1 2026)
| Platform Tier | EV / Revenue | Notes |
|---|---|---|
| Public median (Vertical SaaS) | 6.7x | Q1 2026 baseline |
| Category leaders | 8–12x | Top-quartile vertical SaaS platforms |
| Outliers / category-defining leaders | Up to 14x | Best-in-class with mature embedded fintech |
| Subsector — Healthcare IT | 9.5–12.0x | Regulatory moats + AI integration |
| Subsector — Financial Services | 9.0–11.5x | Embedded banking/lending |
| Subsector — Construction Tech | 7.5–10.0x | Project management + payments |
| Subsector — Retail/Hospitality | 5.5–7.5x | Multiple compression |
| Embedded fintech valuation lift | +25–45% | On top of base vertical SaaS multiple |
| Mature platforms — % revenue from payments + lending | 25–40% | Reference point for “mature” embedded finance |
15. Market sizing reference (updated with UBS Q6.0)
| Metric | Figure | Source / Date |
|---|---|---|
| Total US merchant acquiring net revenue (2025 actual) | ~$37B | UBS “The Question 6.0” (May 4, 2026) |
| Total US merchant acquiring net revenue (2030E) | ~$50B (~6% CAGR) | UBS Q6.0 |
| Total US acquiring volume (2025) | ~$13T | UBS Q6.0 |
| Industry blended net take rate (2025) | ~28 bps | UBS Q6.0 |
| SMB share of US net acquiring revenue | ~70% | UBS Q6.0; corroborated by BCG (~75%) and McKinsey (~2/3rds) |
| Software platforms share of US acquiring revenue (broad) | ~35% (2025) → ~45% (2030) | UBS Q6.0 — replaces Q5.0 33%/2024 → >45%/2029 |
| Software platform share of US SMB acquiring VOLUME | ~70% (2025) → ~84% (2030) | UBS Q6.0 — replaces Q5.0 69%/2024 → 86%/2029 |
| Software platform share of US SMB acquiring REVENUE | ~47% (2025) → ~60% (2030) | UBS Q6.0 — NEW in Q6.0; not separately disclosed in Q5.0 |
| US SMEs using an ISV as primary POS/payments solution | 90% in 2025 (up from ~50% in 2022) | McKinsey 2025 Merchant Acquiring Survey, “Decoding ISV maturity” (Jan 8, 2026); N=1,500+ |
| US SME payments revenue opportunity | ~$27B; ~60% flows through ISVs | McKinsey 2025 |
| SaaS share of SME acquiring revenues | 36% (2024) → 45% (2028) | BCG / Adyen (September 2025) |
| SMB net take rate (2025; UBS estimate) | ~80 bps | UBS Q6.0; forecast +1 bps/yr through 2030 |
| Mid-market & Enterprise net take rate (2025) | ~10 bps | UBS Q6.0; forecast –0.2 bps/yr through 2030 |
| Embedded finance TAM (current) | $185B | Adyen / BCG Embedded Finance Report (2024); Sept 2025 update |
| Embedded finance — untapped portion | ~80% of TAM | Adyen / BCG (2025) |
| Revenue uplift — SaaS + embedded finance vs. SaaS-only | 3–4x subscription revenue | Adyen / BCG (2025) |
| Embedded finance revenue opportunity (NA alone) | $500B+ | Flagship Advisory Partners (2025) |
| Vertical-specific software solutions — share of SME spending | >50% (2023) | McKinsey “Global Payments in 2024” (October 2024) |
| Number of ISVs in US (range of estimates) | 10k (Finix) – 62k (IBIS World 2025) – 92k (ISV World) | Q6.0 cites all three; wide range due to definitional variance |
| Adyen platform volume (H1 2025) | €27B; +28% YoY; net revenue €143.3M (+45% YoY) | Adyen H1 2025 reporting |
| Stripe total payment volume (2025) | $1.9 trillion (+34% YoY) | Stripe 2025 Annual Letter (February 2026) |
| Worldpay PayFac market share | ~75% of all Mastercard PayFac volume | Worldpay / Payrix (post Global Payments / Worldpay merger close, January 2026) |
| SMBs expecting pricing increases (UBS SMB Survey, Sept 2025) | ~50% | UBS Evidence Lab SMB Payments Survey (N=200 US SMBs) |
16. Methodology and sources
This chapter synthesizes data from the following categories of sources, applied in priority order. Where multiple sources report different figures for the same metric, we use the most recent public filing or the most conservative estimate, and flag the discrepancy in the relevant table.
Source priority hierarchy
1. SEC Filings (Priority 1). Public-company 10-K and 10-Q filings via SEC EDGAR. Most recent annual or quarterly filing used.
2. Earnings Calls (Priority 2). Management commentary, updated guidance, take-rate disclosures not in formal filings.
3. UBS Global Research (Priority 3a). Primary external research source. “The Question 6.0” (May 4, 2026 — canonical); “Toast: FinTech Net Take Rate Analysis & Core Payments Framework” (December 17, 2025); “Visa & Mastercard: Adjusted US Volumes vs. Addressable US PCE Analysis” (April 8, 2026); “Vertical SaaS & Embedded Finance: Takeaways from Vertex hosted by Rainforest” (April 15, 2026); “Stripe Annual Letter Fast Take” (February 24, 2026); UBS Evidence Lab SMB Payments Survey (September 2025; N=200 US SMBs).
4. Other Industry Reports (Priority 3b). Rainforest 2026 Vertical SaaS Embedded Payments Benchmarking Study (Q1 2026 field, May 2026 release — first non-vendor independent benchmark on attach/adoption/take rate in vertical SaaS); William Blair — “How Embedded Finance Drives Enterprise Value and Increases Multiples for SaaS Platforms” (September 2025); Windsor Drake Vertical SaaS Valuation Report (Q1 2026); Adyen / BCG Embedded Finance Report (2024 + September 2025 update); Flagship Advisory Partners (2025); BCG / Adyen “Moving Embedded Finance from Promise to Practice” (September 2025); McKinsey “Global Payments in 2024” (October 2024) and “Decoding ISV Maturity: A Global Playbook for Payments Growth” (January 8, 2026; N=1,500+); Mastercard / Cardstream PayFac-as-a-Service White Paper (February 2025); Worldpay Payrix Vertical SaaS Benchmarking Study (January 2025); Clearly Payments Chargeback Benchmarks; Ethoca 2025 State of Chargebacks.
5. Vertical Research (Priority 4). NADA 2024 Data Report (auto repair); Federal Reserve Diary of Consumer Payment Choice (2024); Rentec Direct State of Rent Report 2024; Health & Fitness Association 2025 Benchmarking Report; CMS National Health Expenditures 2024; HomeServiceHound 2025; TouchBistro 2025 State of Restaurants; Mastercard SpendingPulse.
6. Vendor Documentation (Priority 5). Stripe Connect, Adyen for Platforms, Finix, Rainforest, Tilled, Payabli, Worldpay/Payrix, Forward, Infinicept Launchpay, NMI, WePay/Chase public partner-program documentation and pricing pages.
7. Charge Forward Advisory (Priority 6). Directional observations and ranges from Charge Forward advisory engagements. Marked “Charge Forward advisory” where used.
Conflict resolution and flagging conventions
Where multiple sources report different figures: most recent public filing wins, most conservative estimate among comparable figures wins. Discrepancies are surfaced inline with ⚑ FLAG callouts. Net-new findings introduced in this version are surfaced with ★ NEW IN Q2 2026 badges. Figures that cannot be sourced to a primary document carry a ⚑ FLAG and are excluded from board-grade citations.
Data freshness — as-of dates for key data points (updated for v4)
| Data Point | As Of | Source Type |
|---|---|---|
| Toast fintech revenue / GPV / take rate | Dec 2024 (10-K) + Feb 2026 (Q4 2025 earnings) | SEC Filing + Earnings Call |
| Bill.com TPV and transaction fees | Jun 2025 (FY25 10-K, filed Aug 2025) | SEC Filing |
| ServiceTitan GTV and usage revenue | Jan 2026 (FY26 10-K, filed Mar 12, 2026) | SEC Filing |
| Lightspeed GTV / transaction revenue | Mar 2025 (FY25) + Nov 2025 (Q3 FY26) | Earnings Release |
| AppFolio revenue mix / VAS growth | Dec 2024 (FY24 10-K) + Q4 2025 earnings | SEC Filing + Earnings Call |
| UBS Question 6.0 (replaces Q5.0) | May 4, 2026 | UBS Global Research |
| Rainforest 2026 Benchmarking Study (FULL study) | May 2026 release (Q1 2026 field) | Independent industry research |
| McKinsey 2025 Merchant Acquiring Survey | January 8, 2026 (published) | Industry Research |
| UBS Evidence Lab SMB Payments Survey | September 2025 field; reported in Q6.0 May 2026 | Industry Research |
| UBS Adjusted PCE Analysis | April 8, 2026 | UBS Global Research |
| Visa US interchange schedule | October 18, 2025 | Visa Published Schedule |
| Mastercard US interchange schedule | April 11, 2025 | Mastercard Published Schedule |
| Chargeback rates — vertical SaaS | Jan–Nov 2024 (Worldpay Payrix dataset) | Industry Study |
| Valuation multiples — William Blair | 2020–present (transaction database) | William Blair (Sept 2025) |
| Valuation multiples — Windsor Drake | Q1 2026 (January 2026) | Windsor Drake |
| Visa/MA settlement (~10 bps interchange reduction) | Late 2025 announced; court approval pending late 2026 / early 2027 | Company 8-K filings |
| AI & Agentic Payments protocol announcements | 2025–2026 (Visa, Mastercard, Stripe, OpenAI, Google AP2) | Public press releases & protocol docs |
Next-refresh queue (Q3 2026 — items watched for August 2026 refresh)
Items below are on the watchlist for the next refresh. For board-grade citations between now and then, verify these against the most recent quarterly disclosure before publication.
• Toast Q1 2026 earnings (typically released early May 2026) — net take-rate and GPV update.
• ServiceTitan Q1 FY2027 earnings — usage revenue and GTV update.
• AppFolio + Bill.com Q1 2026 10-Qs — VAS growth and TPV updates.
• Adyen FY2025 full-year results (released ~Feb/Mar 2026) — full-year platform volume.
• Worldpay PayFac registration data (2024 was the last public dataset).
• MDL-1720 (Visa/Mastercard settlement) court status — court approval timeline.
• UBS Question 6.0 mid-year follow-on or “The Toast Question” deeper-dive.
• Stripe Q2/Q3 2026 milestones (Capital volume, Revenue Recognition $1B run-rate confirmation).
All figures should be considered directional rather than definitive, and cross-validated against each company’s most recent quarterly filing before use in investment decisions, board presentations, or vendor negotiations.
17. AI & Agentic Payments benchmarks
Reference data for Chapter 12. AI inside the rails (fraud, routing, underwriting, personalization) is current-state. Agentic payments moved from research demos to live production protocols in 2025–2026. The Rainforest 2026 study added the first independent measurement of AI use case adoption across the maturity-stage spectrum.
17a. AI-inside-the-rails performance benchmarks
| Application | Provider / Source | Measured Impact | Notes |
|---|---|---|---|
| Real-time fraud scoring | Stripe Radar | Hundreds of $B annually scored across millions of merchants | Network-effect ML model; per-payment risk scoring in milliseconds |
| Authorization rate uplift | Stripe Adaptive Acceptance / Adyen RevenueAccelerate / Checkout.com Intelligent Acceptance | +1–3 percentage points incremental auth rate | Captured by processor under flat-rate; flows to platform under IC+ / PayFac |
| Agentic checkout completion | OpenAI + Stripe (DALL·E checkout) | ~40% faster payment completion via AI autofill | Disclosed in Stripe 2025 Annual Letter |
| Embedded credit — default reduction | Sezzle “Prophet” model | 3.2% → 1.8% default rate (12-month cohort) | AI underwriting replaces rule-based model |
| Embedded credit — disbursement scale | Block / Square Loans | >$10B disbursed since launch | Payment-data-underwritten SMB lending |
| Embedded credit — disbursement scale | Shopify Capital | >$5B extended; >70M data points per merchant | Vertical SaaS embedded lending benchmark |
| Embedded credit personalization | Affirm AdaptAI (2025 launch) | Real-time APR/term/eligibility tailoring per consumer | AI-driven offer personalization at point of sale |
| Vertical SaaS chargeback rate (AI fraud) | Worldpay/Payrix all-client average | 0.04% across vertical SaaS book | Vertical specificity + AI underpins below-market chargeback rate |
17b. Agentic-payments timeline — production protocols shipped 2025–2026
| When | Who | What Shipped | Why It Matters |
|---|---|---|---|
| April 2025 | Visa | Visa Intelligent Commerce — open SDK for AI agents to transact on Visa rails with tokenized credentials | Network-level agent enablement at Visa |
| April 2025 | Mastercard | Mastercard Agent Pay — agentic-tokenization framework with Microsoft and IBM partnerships | Network equivalent at Mastercard |
| May 2025 | Stripe | Stripe Agent Toolkit — open-source SDK for LLM frameworks to handle payments end-to-end | First infrastructure for embedding payment capability directly inside LLM agents |
| 2025 | OpenAI + Stripe | Instant checkout in ChatGPT — millions of weekly users complete merchant purchases in-conversation | Largest consumer AI surface now has payments built in by default |
| Sept 2025 | Google + 60+ partners | Agent Payments Protocol (AP2) — open spec for agent-to-agent commerce | First serious cross-industry agentic commerce standard |
| 2025–2026 | Multiple | A2A commerce protocols, MCP-driven payment tools, agent-readable product feeds | Substrate for agents to discover, compare, and transact at internet scale |
17c. AI use cases in payments by maturity stage (NEW — Rainforest 2026)
★ NEW IN Q2 2026 — First independent dataset on AI use case adoption Rainforest 2026 measured which AI use cases vertical SaaS platforms are deploying, segmented by maturity stage. Notable result: fraud detection and auto-reconciliation are the most-deployed at Scaling/Optimized; intelligent routing concentrates at Optimized. Equally notable: the data found NO correlation between AI use and benchmark performance — AI use is increasing, but it has not yet translated into measurable attach, adoption, or take-rate uplift in the cross-section. Early days.
| AI use case | Emerging | Scaling | Optimized | Notes |
|---|---|---|---|---|
| Fraud detection | Low | High | High | Most common AI deployment at scale |
| Auto reconciliation | 24% | ~75% | ~75% | Big jump from Emerging to Scaling; flatlines at Optimized |
| Workflow automation | 47% | 52% | 75% | Grows steadily with maturity |
| Cash flow forecasting | Mid | Mid | Mid | Consistent middle-tier deployment |
| Auto collections | Mid | Mid | Mid | Consistent middle-tier deployment |
| Intelligent payment routing | Low | 23% | 34% | Concentrates at Optimized (requires transaction-level visibility) |
| Customer support / chat | Mid | Mid | Mid | Consistent middle-tier deployment |
| Personalized insights | Low | Mid | Mid | Adoption grows with maturity |
| Underwriting (embedded credit) | Low | Mid | Mid | Tied to embedded-lending program presence |
| Not yet using or planning AI | ~33% | Lower | Very low | ~1 in 3 Emerging platforms still have not started |
17d. AI & Agent Readiness diagnostic
From Chapter 12. Three concrete tests for whether a vertical SaaS platform is positioned to participate in agentic commerce. Almost no platform answers “yes” to all three today. Targets for end of 2026:
• Can an external service programmatically retrieve a structured product/service catalog for one of your merchants? (Test of agent discoverability.)
• Can an external service initiate and complete a payment to a merchant on a credentialed customer’s behalf, with delegated authentication and tokenized credentials? (Test of agent transactability.)
• Does your reporting distinguish agent-originated transactions from human-originated transactions? (Test of agent observability.)
18. Consolidated cross-chapter reference tables
Reference tables surfaced in body chapters that other chapters cross-link to. Consolidated here so every chapter cites a single source.
18a. L2/L3 commercial-card impact — GMV × commercial mix grid (from Ch 6)
Annual savings from Level 2 and Level 3 data submission on commercial-card transactions. Savings shown at 25 bps (L2) and 50 bps (L3) on qualifying commercial-card volume.
| Annual GMV | Commercial Card Mix | L2 Savings (25 bps) | L3 Savings (50 bps) |
|---|---|---|---|
| $50M | 10% (~$5M) | $12,500 | $25,000 |
| $50M | 20% (~$10M) | $25,000 | $50,000 |
| $50M | 30% (~$15M) | $37,500 | $75,000 |
| $100M | 10% (~$10M) | $25,000 | $50,000 |
| $100M | 20% (~$20M) | $50,000 | $100,000 |
| $100M | 30% (~$30M) | $75,000 | $150,000 |
| $250M | 10% (~$25M) | $62,500 | $125,000 |
| $250M | 20% (~$50M) | $125,000 | $250,000 |
| $250M | 30% (~$75M) | $187,500 | $375,000 |
| $500M | 10% (~$50M) | $125,000 | $250,000 |
| $500M | 20% (~$100M) | $250,000 | $500,000 |
| $500M | 30% (~$150M) | $375,000 | $750,000 |
18b. US network assessment fees reference (from Ch 6)
| Fee Name | Network | Rate | Trigger |
|---|---|---|---|
| Assessment (brand usage) — Credit | Visa US | ~0.14% of volume | Per Visa credit transaction |
| Assessment (brand usage) — Debit | Visa US | ~0.13% of volume | Per Visa debit transaction |
| APF — Credit Auth | Visa US | $0.0195 per auth | Per Visa credit authorization |
| APF — Debit/Prepaid Auth | Visa US | $0.0155 per auth | Per Visa debit/prepaid authorization |
| FANF (Fixed Acquirer Network Fee) | Visa US | Variable by merchant; tiered by channel & MCC | Per merchant tax ID |
| NABU (Network Access & Brand Usage) | Mastercard US | $0.0195 per auth | Per Mastercard credit/sig-debit auth |
| Cross-Border Assessment | Visa / MC US | 0.60% (USD settled); 1.00% (non-USD) | Non-US-issued cards used at US merchants |
| Acquirer Service Fee | Visa Canada | 0.09% of volume | All Visa cards acquired in Canada |
| Acquirer Volume Assessment | Mastercard Canada | 0.090% (9 bps) | Assessable Mastercard volume in Canada |
18c. Embedded finance six-stage product matrix (from Ch 8 / Ch 10)
| Stage | Product | Data That Enables It | Typical Revenue Uplift |
|---|---|---|---|
| 1 | Payment Acceptance | Baseline — no prior data required | 30–40% of total platform revenue at maturity |
| 2 | Working Capital / MCA | Daily GPV, seasonal patterns, revenue consistency | 10–15% additional revenue per activated merchant |
| 3 | Term Lending | 12–24 mo transaction history, receivables, default rates | 8–12% additional revenue per activated merchant |
| 4 | Insurance | Chargeback history, transaction risk profile, operations | 5–10% additional revenue via referral / underwriting share |
| 5 | Banking / BaaS | Full transaction history, cash flow patterns, payroll | 15–25% additional revenue as primary banking relationship |
| 6 | Payroll | Workforce size, payroll frequency, payment volume, tax | 10–20% additional revenue; dramatically increases switching cost |
18d. Embedded finance infrastructure landscape (from Ch 10)
| Category | Key Companies (illustrative) | Count |
|---|---|---|
| Embedded Payments Platforms | Stripe, PayPal, Block, Adyen, Fiserv, FIS, Global Payments, J.P. Morgan Payments, Nuvei, Fortis, Rapyd, Airwallex, Checkout.com, WePay, BlueSnap | 25+ |
| Banking-as-a-Service (BaaS) | Unit, Treasury Prime, Synctera, Green Dot, Helix by Q2, Cross River Bank, Goldman Sachs Transaction Banking, Evolve Bank, Pathward, The Bancorp, Mambu, Thought Machine, Griffin, Pismo | 25+ |
| Embedded Lending & BNPL | Affirm, Klarna, Afterpay, YouLend, Lendflow, Parafin, Liberis, Wisetack, TreviPay, Kanmon, Pipe, Capchase, Outfund, FundThrough, Raistone | 20+ |
| Embedded Insurance | Next Insurance, Pie Insurance, Coterie, Vouch, Boost Insurance, Ascend, Sure, Branch, Cowbell Cyber | 10+ |
| Embedded Payroll | Gusto Embedded (Check), Toast Payroll, Homebase, Rippling, Justworks, Paylocity, Patriot Software | 10+ |
| Spend Management & Cards | Divvy/BILL, Brex, Ramp, Marqeta, Lithic, Stripe Issuing, Galileo, i2c, Deserve | 10+ |
For questions, discrepancies, or to report updated figures, contact payments.chargeforward.io. This chapter is updated quarterly. Next refresh: August 2026.
The standalone Embedded Payments Maturity Framework download is at chargeforward.io/resources. Run platform-specific economics modeling via the Payments Revenue Calculator at chargeforward.io/tools.