40 of 216 answers described a Nordic bank’s withdrawn credit line as on sale (11 Sept to 8 Oct 2026)

    Get recommended.
    With the right terms.

    AI assistants now quote your rates, fees and products to customers. Honeyb checks those answers against your published terms, corrects the sources behind the wrong ones and gets you recommended.

    AI search visibility, grounded in your published terms.

    Product
    Market
    Engine
    ClaudeNorwayNorwegianCaptured 3 Oct 2026

    AskedWhat are [the lender]'s terms on its personal loan? Amount, rate and fees.

    Lånebeløpet er mellom 10 000 til 500 000 kr25 000–400 000 kr. Den nominelle renten ligger mellom 8,•• - 19,•• %12,••–16,•• %, mens den effektive renten er mellom 8,•• - 24,•• %from 12,•• %.

    Checked against published terms3 of 3 wrong
    • Loan amountPublished: 25,000 to 400,000 krDiffers
    • Nominal ratePublished: 12.•• to 16.•• %Differs
    • Effective ratePublished: Cannot start below the 12.•• % nominal floor; 18.•• % in the published exampleDiffers

    A real answer, captured 3 Oct 2026. Institution names and identifying digits are masked. How this was checked

    AI answers about banks and lenders captured
    7,530
    AI answers about banks and lenders captured
    claims extracted and checked against published terms
    5,725
    claims extracted and checked against published terms
    markets: Finland, Sweden, Norway, the UK and the EU
    5
    markets: Finland, Sweden, Norway, the UK and the EU
    languages: English, Finnish, Swedish and Norwegian
    4
    languages: English, Finnish, Swedish and Norwegian

    Honeyb’s finance measurement on ChatGPT, Gemini, Claude and Perplexity, 11 Sept to 8 Oct 2026.

    The ledger

    The claim. The terms. The evidence.

    The claims from the answers above that did not match, beside the published terms. Open a row to read the answer.

    12 answers · 27 claims checked by hand · 18 match · 7 differ or outdated · 2 cannot verify

    How an answer is checked

    1. 01Capture. The question is asked in the market's language on each assistant, and the answer is kept with its date.
    2. 02Extract. An accuracy model pulls out each product claim: rate, fee, amount, term, availability, licence.
    3. 03Compare. Each claim is compared with the terms the institution published, as recorded on the capture day.
    4. 04Re-read. Anything we publish is re-read by a person. Where the terms cannot settle it, it is marked Cannot verify.

    Measured over time

    Answers change from one capture to the next.

    A single audit is a snapshot. The work is watching the answers move, and acting when they do. Drag across the capture days.

    24 September 2026

    5 / 12

    answers described the withdrawn credit line as on sale. 6 said it was withdrawn.

    40 of 216 answers across 18 capture days. Each one re-read by a person.

    11 Sept24 Sept8 Oct
    Described as on sale Said it was withdrawn Hedged or no answer

    How the work gets done

    From a wrong answer to a corrected source.

    We work as your agency. Honeyb finds the claim, traces the source the assistants are reading, proposes the fix and does the work once your team approves it.

    Example workflow
    1. FoundHoneybStep 1

      Two assistants describe a credit line withdrawn in March 2025 as on sale. Both quote terms from a 2021 information sheet.

    2. ProposedHoneybStep 2

      Retire or redirect outdated product documents. Add structured terms to the current product page. Send correction requests to the comparison sites the answers cite.

    3. ApprovedYour teamStep 3

      Compliance and marketing review the proposal against the published terms. Nothing changes until they sign off.

    4. PublishedHoneybStep 4

      Page changes go live through your CMS. Correction requests are sent and tracked to a reply.

    5. Re-checkHoneybStep 5

      The same questions run again in each market and language. The next sample shows whether the answers moved.

    Built for regulated teams

    Evidence your compliance team can read.

    Dated evidence

    Every comparison keeps its capture date, the answer and the terms it was checked against, so risk and marketing review the same record.

    You approve every change

    Nothing about your products is published without your team. We propose; your reviewers decide.

    Your markets, your languages

    The Nordics, the Baltics, the UK and the EU, asked in the language your customers use.

    See the public Latvia example
    Part ofMastercard LighthouseNVIDIA Inception Program Member

    The accuracy audit

    Start with your products. Leave with the corrections made.

    What you get

    • 01Answers from 8 AI assistants about your priority products, in your market's language
    • 02Each rate, fee and availability claim checked against your published terms
    • 03The sources behind every mismatch, and the corrections we will make

    A paid audit. We agree the scope, timing and fee with you before we start, and we do the correction work, not just the report.

    We will check what 8 AI assistants say about your products in Finland, against your published terms.

    Prefer to talk? Speak to Founder

    Questions

    What does the accuracy audit include?

    A defined sample of AI answers about your priority products, in your markets and languages. Each rate, fee and availability claim is checked against your published terms, with the sources behind every mismatch and a prioritised correction plan that we then carry out. We agree the products, markets and fee before starting.

    Can Honeyb change an AI answer directly?

    No one outside the AI provider can. We improve the source information the assistants read: your own product pages, outdated documents still online, and third-party comparison pages, where we send correction requests. Then we measure the answers that follow.

    How do you decide whether a claim is wrong?

    We compare it with the terms published for that product, market and date. A mismatch needs supporting evidence. Where the published information cannot settle it, the claim is marked Cannot verify rather than wrong, and findings we publish are re-read by a person.

    How quickly do corrections show up in AI answers?

    It depends on the source, the publisher and the assistant. We record the date a source changes separately from what later answer samples show, so you can judge the effect for yourself.

    What do you need from us?

    Your website and priority markets are enough to scope the audit. We work from public product information, so no customer data or system access is needed. For changes to your own pages, we need a reviewer on your side.