Industry — B2B fintech
When a finance lead asks an AI which provider to use, are you in the answer?
Payments, banking APIs, expense management, accounting automation, KYC and AML, fraud technology, lending infrastructure. Categories where buyers shortlist by research, and where the shortlist is increasingly assembled by a machine.
The pattern we expect to find
Strong brand, thin evidence, invisible in the answer.
These are hypotheses shaped by how the category is structured, not claims about your company. The audit is how we find out which apply to you.
- Excellent product pages, and no comparison or alternatives content — because legal was nervous about naming competitors and the conversation ended there.
- Pricing behind “contact sales”, which means every answer about your cost is assembled from third parties and guesswork.
- Deep regulatory expertise inside the company and almost none of it published.
- Aggressive bot management, entirely reasonable for a financial platform, that also blocks the crawlers deciding whether you exist.
- Category ambiguity — you call yourself spend management, the market calls it expense software, the models are not sure you are the same thing.
- A review platform profile last updated two years ago, being cited today.
Compliance reality
The constraint that actually governs delivery.
In regulated fintech the bottleneck is almost never ideas or writing. It is the approval path. We plan around it explicitly instead of discovering it in month two.
Review time is scoped, not assumed
We agree the approval path during onboarding: who reviews, what turnaround is realistic, and which content classes need legal versus compliance versus neither. Then we build the calendar around that, not around a fantasy.
Reactive commentary needs a pre-agreed lane
Commenting on a regulatory development within a day is worth a great deal and impossible without pre-approved boundaries and a named approver who can act quickly. We set that up before we need it.
Accuracy is the standard, not a risk
Content that overstates what a licence permits or what a control guarantees is a genuine problem, not a growth tactic. Our editorial standard on regulatory claims is stricter than the marketing norm, which usually makes the compliance conversation shorter rather than longer.
Query space
What a fintech query set looks like.
Illustrative examples of the classes we build from. Your actual set is generated from your product, customers, markets and competitors, then agreed with you before anything runs.
- best payment orchestration platform for marketplaces
- stripe alternatives for european businesses
- expense management vs corporate card providers
Where AI answers are most influential and where most fintechs have no content at all.
- kyc provider for crypto exchanges
- banking api for embedded finance startups
- fraud detection for high-volume card-not-present
Buyers describe their situation, not your category. This is where specificity wins.
- expense platform that integrates with netsuite
- migrating from legacy payment gateway
- which providers support open banking in germany
High commercial intent, frequently answered from documentation rather than marketing pages.
- what does psd2 sca require for recurring payments
- how long must kyc records be retained
- difference between emi licence and banking licence
Genuine demand, answerable by your compliance team, and almost never published.
- how much does kyc verification cost per check
- typical interchange plus pricing
- what do fraud tools cost for a mid-market merchant
Most fintechs publish nothing here, so the answer gets assembled entirely from third parties.
Engagement shape
What the first ninety days look like in a fintech.
The sequence is deliberate: unblock access first because it is fast and provable, then evidence, then content, because content published into a site nothing can read is a waste of your SME's time.
- 01
Weeks 1–2 — Access and baseline
Credentials, analytics, Search Console. Query set and competitor set agreed. Baseline measured and locked before a single change ships. - 02
Weeks 2–4 — Accessibility and entity
Crawler access at the edge, rendering on commercial templates, canonical description agreed and rolled out across every external profile. Fast, provable, and usually overdue. - 03
Weeks 3–6 — Extraction sessions
Interviews with solutions engineering, compliance and support. This is where the material that nobody else can publish comes from. - 04
Weeks 5–10 — First content and approval loop
Comparison and alternatives content, plus the regulatory explainers your team already knows cold. First pass through the approval path, deliberately, so we learn its real speed. - 05
Weeks 6–12 — Authority
Review platform profiles completed and a legitimate review programme started. Industry media and expert commentary opportunities identified, approved and pitched by a human. - 06
Week 12 — Second measurement
Same query set, same method. Enough to see direction. Not enough to declare victory, and we will not pretend otherwise.
Find out where you actually stand.
The audit gives you a query-level baseline across ChatGPT, Gemini and Perplexity, a competitor set built from what the models actually say, and a prioritised list of what is causing the gap.