Fintech AI Visibility Index 2026

Stripe, Inc. leads this fintech roll-up with a 36.6% appearance rate across 1,161 returned answers. PayPal follows at 33%, and Adyen ranks third at 25.4%. These results describe the measured fintech prompts on September 14, 2026, not consumer demand across the category.

The gap between Stripe and PayPal is within the margin of this sample because their 95% intervals overlap. The same caution applies across other overlapping intervals. A brand's place in this report measures how often an engine named it, not whether it is the best consumer selection.

Which fintech brands appear most often?

Stripe ranks first, followed by PayPal, Adyen, Fidelity, and The Charles Schwab Corporation. Stripe appeared in 425 returned answers. PayPal appeared in 383, while Adyen appeared in 295. Appearance rates use 1,161 returned answers as the denominator.

Stripe's 95% interval is 33.9% to 39.4%. PayPal's is 30.3% to 35.7%, so the two intervals overlap. Stripe's interval also overlaps Adyen's 23% to 28% only at no point, while PayPal's interval does not overlap Adyen's. The measured gap between the first two brands remains within this sample's margin.

Appearance rate is the share of the 1161 returned AI answers in which each brand was named.

Intervals overlap among several adjacent ranks. Fidelity's 18.7% to 23.4% interval overlaps The Charles Schwab Corporation's 17.1% to 21.7% interval, Robinhood's 15.6% to 20% interval, Klarna's 15.3% to 19.7% interval, and Affirm's 15.2% to 19.6% interval. Do not treat those overlaps as proof that one brand is more visible than another.

Stripe, Inc.

Where do the engines disagree?

The engines disagree most for brands whose visibility is concentrated in Perplexity or ChatGPT. Each engine uses a different model and retrieval tool, so a gap can reflect system design rather than a stable difference in brand visibility.

Each cell uses that engine's own answer count as its denominator, so engines can be compared row by row.

Airwallex is the sharpest single-engine pattern. Perplexity named Airwallex in 24.1% of 291 answers, compared with 0.7% of 289 ChatGPT answers, 2.4% of 291 Gemini answers, and 3.1% of 290 Claude answers. Square also has a Perplexity-weighted pattern: 24.7% in Perplexity versus 16.6% in ChatGPT, 10.3% in Gemini, and 10% in Claude. Helcim appeared in 18.9% of Perplexity answers but 7.3% of ChatGPT answers, 14.8% of Gemini answers, and 4.1% of Claude answers.

Some brands were absent in specific engines. Splitit appeared in 16.8% of Perplexity answers, 15.9% of ChatGPT answers, and 8.6% of Gemini answers, but in none of Claude's 290 answers. Authorize.Net appeared in Perplexity, ChatGPT, and Gemini answers but not Claude answers. SoFi Technologies, Inc. and Block were also absent from Claude's 290 answers. ETRADE was absent from Gemini's 291 answers but appeared in 7.9% of Perplexity answers, 14.5% of ChatGPT answers, and 6.2% of Claude answers. Firstrade appeared only in Perplexity, at 4.1% of 291 answers.

At the top, Perplexity and ChatGPT named Stripe, PayPal, and Adyen more often than Gemini and Claude. Claude's rates were lower for Stripe, PayPal, Adyen, Robinhood, Klarna, and Affirm. The differing engine totals matter: Perplexity returned 291 answers, ChatGPT 289, Gemini 291, and Claude 290.

Which demand clusters favor which brands?

The demand-cluster view separates broad selection questions from more specific need questions. It shows where a brand appears in the measured query groups, rather than treating all fintech questions as interchangeable.

Read the grouped clusters independently. A brand that leads a general buyer-intent group has a different measured strength from a brand that leads a sub-category or specific-need group. The chart supports planning by question type, not a claim that one type of demand matters more than another.

Which sites do engines cite for fintech answers?

Owned-domain citation rates use 1,158 answers with retrieval evidence as the denominator. Shopify Inc. had the highest measured owned-domain citation rate among listed brands at 12.3%, followed by Airwallex at 11.9%, Fidelity at 7.7%, and Stripe and PayPal at 6.6% each.

Share of the 1158 answers with retrieval evidence that cited a URL on the brand's own website.

Appearance and owned-domain citation are different measures. Shopify appeared in 12% of returned answers but its domain was cited in 12.3% of evidence-backed answers. Airwallex appeared in 7.6% of returned answers and its domain was cited in 11.9% of evidence-backed answers. The measured tally therefore separates brand naming from source selection.

Publishers cited across fintech answers

Third-party publishers appear often in the evidence set. Forbes was cited in 36.1% of 1,158 answers with retrieval evidence, NerdWallet in 27.5%, ConnectPay in 23.6%, CNBC in 21.3%, and Reddit in 16%.

Publishers cited as evidence, counted once per answer rather than once per link.

The source pattern includes editorial, comparison, community, and company domains. Forbes had 418 cited-answer mentions, NerdWallet had 318, ConnectPay had 273, and CNBC had 247. Airwallex.com and Shopify.com also appear among the listed sources, with 138 and 133 cited-answer mentions.

Who is winning and who is at risk?

Measured leaders

Stripe leads the roll-up at 36.6% appearance, with an average first mention position of 2.5 and 100% cross-engine consistency. PayPal follows at 33% appearance and 100% cross-engine consistency. Adyen ranks third at 25.4% appearance, also with 100% cross-engine consistency. Fidelity ranks fourth at 20.9%, has an average first mention position of 2.6, and its owned domain was cited in 7.7% of evidence-backed answers.

Shopify has a distinct source-strength result. It ranks 15th in appearance at 12%, but its owned-domain citation rate is 12.3%, the highest listed rate. Airwallex ranks 23rd in appearance at 7.6% and has an 11.9% owned-domain citation rate, although its engine pattern is concentrated in Perplexity.

Measured exposure risks

Block appeared in 7.1% of returned answers and its owned-domain citation rate was 0% of evidence-backed answers. Firstrade appeared in 1% of returned answers, was named only by Perplexity, and had 25% cross-engine consistency. Block/Square and Tradier each had a 0% appearance rate in the 1,161 returned answers.

Claude gaps are another exposure risk in this sample. Splitit, Authorize.Net, SoFi Technologies, Inc., and Block were each named in 0% of Claude's 290 answers. ETRADE was named in 0% of Gemini's 291 answers. These gaps do not establish a category-wide outcome, but they identify engine-specific blind spots for the measured prompts.

What does the category pattern show?

The top of the fintech leaderboard is led by payments, investment, and consumer-credit brands. Stripe, PayPal, Adyen, Fidelity, The Charles Schwab Corporation, Robinhood, Klarna, and Affirm fill the first eight ranks. The tally does not establish market standing outside the measured prompts.

The top two results remain statistically close within this sample. Stripe's 33.9% to 39.4% interval overlaps PayPal's 30.3% to 35.7% interval. Stripe's interval does not overlap the intervals for Adyen, Fidelity, or The Charles Schwab Corporation. At lower ranks, overlap is common and ranking claims need restraint.

Cross-engine coverage is broad for many leading brands. Stripe through Braintree each have 100% cross-engine consistency except Splitit, Authorize.Net, SoFi Technologies, Inc., Block, ETRADE, and TradeStation, which each have 75%. Firstrade has 25%. Owned sites do not dominate the cited-source list. Forbes, NerdWallet, ConnectPay, CNBC, Reddit, Whop, and StockBrokers each appear ahead of most owned domains by cited-answer mentions.

What changed during the measurement window?

This tally is a cross-segment roll-up from 1,161 measured answers. It does not include an earlier measurement wave, so it does not document movement over time. It does show engine-level divergence within the window, including Airwallex's 24.1% Perplexity rate against lower rates in the other three engines.

What should fintech brands test next?

• Audit Perplexity-only strength where it appears. Airwallex had 24.1% appearance in Perplexity but 0.7% in ChatGPT, 2.4% in Gemini, and 3.1% in Claude. Re-run the same prompt set by engine after publishing clear product and comparison pages.
• Close engine-specific absence gaps. Splitit, Authorize.Net, SoFi Technologies, Inc., and Block were absent from Claude answers. Re-measure their Claude appearance rate and cross-engine consistency after source and entity cleanup.
• Test owned-domain citation pages for brands with no measured citation rate. Block and Firstrade each had a 0% owned-domain citation rate. Re-measure citations against the 1,158-answer retrieval-evidence denominator.
• Separate source work from name-recognition work. Shopify had 12% appearance and a 12.3% owned-domain citation rate. Compare both measures after adding pages that state product scope, fees, eligibility, and selection criteria in plain language.
• Review top publisher coverage. Forbes, NerdWallet, ConnectPay, and CNBC were cited in 36.1%, 27.5%, 23.6%, and 21.3% of evidence-backed answers. Re-measure whether brand pages and independent coverage appear in the same answer set.
• Test prompt clusters separately. Use the cluster result to check whether a brand appears for broad selection questions, specific-need questions, or both. Re-measure the same clusters rather than relying on an overall rate alone.

What does this mean for fintech brands?

Interpretation: fintech visibility varies by engine, question type, and evidence source. A strong overall appearance rate can coexist with weak owned-domain citations. A strong owned-domain citation rate can coexist with a lower overall appearance rate.

Interpretation: brands need two checks. Track whether engines name the brand in returned answers. Track whether the brand's own domain is cited when retrieval evidence is present. The study does not prove what content change will improve either measure. It provides a baseline for repeat measurement.

How was this fintech AI visibility measured?

This flagship roll-up tallies 99 prompts across Perplexity, ChatGPT, Gemini, and Claude. Each prompt ran three times per engine. The study attempted and returned 1,161 answers, with 1,158 answers carrying retrieval evidence. Appearance rates use returned answers. Citation and source rates use answers with retrieval evidence.

How this study was measured

• Sampling frame fixed first: 99 prompts allocated across the demand clusters before anything was asked.
• Same questions put to every engine: Perplexity (sonar-pro), ChatGPT (OpenAI), Gemini (Google), Claude (Anthropic), 3 trial(s) each.
• 1161 answers returned of 1161 attempted, 1158 with retrieval evidence.
• Product lines rolled up to parent brands using a registry fixed before scoring.
• Appearance rate reported with a 95% Wilson interval; citation metrics counted only on answers with evidence.

The report aggregates four segment studies and only ranks categories measured in those segments. The reported results apply to these prompts on the measurement date. Engine differences may result from the model and retrieval tool each system uses. Three answers lacked retrieval evidence, and no answers failed.

Charts and data tables

These are not brands in the category, so they are measured the same way but kept out of the brand leaderboard.

Methodology appendix

This appendix is generated directly from the measurement record for this study. It is included so any brand named here can reproduce or challenge the result.

What was measured

• Category: Fintech
• Measurement date: 2026-09-14
• Depth: flagship — 99 prompts, 3 trial(s) per prompt per engine, 4 engines
• Answers attempted: 1161
• Answers returned (appearance denominator): 1161
• Answers with retrieval evidence (citation denominator): 1158 (99.7% of attempted)
• Answers that failed outright: 0
• Analysis version: study-methodology-v2 · entity registry: entity-registry-2026-08-27

Claim limit: Cross-segment roll-up: every figure in this hub is tallied from the 1161 measured answers of its 4 segment studies. No figure here is estimated, and no category is ranked that was not measured in one of those segments.

How the prompts were sampled

Results are not strictly comparable across engines: each engine uses a different model, a different retrieval tool and a different answer format, so a gap between two engines can reflect system design as much as brand visibility.

How each metric is defined

• Appearance rate — the share of returned answers that named the brand. Measured on every answer the engine returned, whether or not it searched the web, so an engine's retrieval behaviour does not silently change the denominator.
• Macro appearance rate — the mean of the per-prompt appearance rates, so each prompt counts once regardless of how many engines answered it.
• 95% interval — Wilson score interval on the appearance rate. Where two brands' intervals overlap, this study does not support a claim that one is more visible than the other.
• Owned-domain citation rate — the share of answers with retrieval evidence that cited a URL on the brand's own domain. This is a narrow measure of the brand's own site being used as a source; it is not a measure of total mentions.
• Share of all citations — the brand's own domain as a share of all attributed publisher citations in the study.
• Not measured — the brand's official domain could not be established, so no citation result exists. This is never reported as 0%.
• 0% — the metric could be evaluated and the event did not occur.
• Average position — mean position of the brand's first mention in the answer's ordered list of named brands.
• Cross-engine consistency — the share of engines that named the brand at least once.
• Repeat consistency — the share of repeated prompt/engine cells where the brand appeared in every trial. Lower values mean the engine's answer is unstable rather than the brand being absent.

Evidence rules

• An answer counts as having retrieval evidence only when the engine returned a retrieval receipt (search annotations or grounding records). A URL the model merely typed into its prose is not treated as evidence that it searched.
• Sources are attributed to the publisher behind each retrieval receipt. Intermediary and redirect hosts are never reported as publishers.
• Publisher identity could not be established for 19 retrieval receipt(s); those are disclosed here rather than attributed or dropped.
• Source counts are answer-level: a publisher counts once per answer in which it was cited, not once per URL.

Entity handling

Product lines and model names roll up to their parent brand for brand-level metrics, using a registry fixed before scoring. Nothing is merged on the basis of this study's own counts alone.

No roll-ups were applied in this study.

40 further name(s) picked up in the answers were not confidently resolvable to a brand in this category and are held for human classification before the next study; they carry no metrics here.

Limits of these findings

• This is a point-in-time measurement of what the named systems returned for these exact prompts on 2026-09-14. Engine behaviour changes without notice.
• The prompt set is a stratified sample of category demand, not a census. Results describe these prompts and should not be read as representative of all searches in the category.
• Where intervals overlap, differences between brands are not statistically distinguishable at this sample size.
• A brand not listed here was not measured as absent — it simply was not named in these answers.
• Appearance is a visibility measure, not an endorsement, a quality judgement or a market-share estimate.

The segment reports in this family

Each segment below was measured separately, with its own brand panel and its own question set, and has its own report. The figures in this table come from those segment measurements.

Segment reports

Related indexes already published

These categories were measured in earlier published indexes and are not re-measured here. Any figure below is quoted from the page it links to, on that page's own methodology and date.

• Neobanks AI Visibility Index 2026 — The world’s largest neobank commands 55% of Latin America’s AI visibility — and effectively disappears when the conversation crosses into the United States.. Figures as published on that page: 01 34.7%, 02 14.2%, 03 9.8%, 04 7.9%.
• Crypto AI Visibility Index 2026 — Crypto & Digital Assets AI Visibility Index 2026
• Wealth AI Audit 2026 — The Wealth AI Audit

Where this index is linked from

• Financial services and fintech PR — the practice page for fintech public relations and AI search visibility programs.
• Fintech marketing agency services — integrated fintech marketing, content, and generative engine optimization.
• Pre-IPO financial communications — investor and media communications for pre-IPO fintech companies.