Case study · Fintech and digital banking · CEE and Nordic

One brand, a different story in every language

A multi-market digital bank was a trusted challenger in one country and "limited and regional" in the next. AI's story changed by language, and it cost shortlist places. How it reached one consistent, recommendable narrative in 90 days.

The interactive report

The same AI Visibility report we deliver to clients. Use space or the arrow keys to move through it.

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What we measured

Test prompts
110
AI models
Gemini, ChatGPT
Personas
5 personas across 4 languages: retail switcher, SME owner, cross-border sender, freelancer, security-conscious new user
Competitor benchmark
6: two global neobanks, one transfer specialist, two incumbent banks, one local challenger

Results after 90 days

MetricStartDay 90Change
AI Visibility Score29/10052/100+23 pts
Prompt Impression Rate31%54%+23 pp
Share of AI Answer vs competitors12%26%+14 pp
Semantic Match Rate45%71%+26 pp
Narrative Consistency33%69%+36 pp
Brand Recommendation Rate22%38%+16 pp
Content Gap Index67/10036/100-31 pts

Key findings

AI's description changed by language: a trusted challenger in one market, "limited / regional" in another.

The brand contradicted itself across markets it was trying to win.

The most critical-toned answers came in the Germanic-language prompts.

Strong markets read coolest, suppressing recommendation.

Recommendation share sat near the bottom of the peer set.

A solid product, but AI lacked confirming signals.

Safety, licensing and deposit-guarantee questions were answered vaguely.

AI hedged on trust, the gate to a financial recommendation.

The 90-day plan

Month 1: narrative foundation

Define one cross-market narrative with the same trust facts (licensing, deposit guarantee) in every language; remove the drift.

Month 2: content for AI intents

Per-market, per-persona decision content: fees, best-app-for, and safety/regulation explainers, localized for each language.

Month 3: external signals

Local fintech media in each market, comparison sites, trust references, a cross-border money report, monthly re-measurement across languages.

Before and after

AreaBeforeAfter 90 days
VisibilityVisible at home, thin elsewhere.Surfaces across markets and personas.
NarrativeA different story in each language.One consistent story: a licensed digital bank.
CompetitionGlobal neobanks owned the shortlists.Holds its place as a regional challenger.
ContentMarketing pages, vague on trust.Content answers safety, fees and persona intents per market.
EvidenceFew local signals confirming trust.Local media and comparison sites raise confirmation.

Method. Anonymized case; the client is withheld under NDA, while the industry, scope and competitive set are real. Baseline figures are drawn from Rankfor's AI-visibility index measurements in fintech and digital banking (CEE and Nordic); the 90-day figures reflect the trajectory the Rankfor program is built to produce. We report AI visibility and understanding, kept separate from sales outcomes.

FAQ

Why did AI describe the same bank differently per country?

AI reads each market in its own language from local sources. Where the trust facts and positioning were not stated consistently, AI told a different story per language, calling the brand a trusted challenger in one market and "limited" in another.

What changed in 90 days?

One cross-market narrative with the same licensing and deposit-guarantee facts in every language, per-market decision content, and local fintech-media coverage. Narrative Consistency rose the most, and AI Visibility rose from 29 to 52 of 100.

Do these figures reflect account openings?

No. The baseline comes from Rankfor's Nordic-Baltic AI Reputation Index (four grounded models, multiple languages). The figures measure AI visibility and understanding, kept separate from account openings.

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