Highlights
- The dataset: Over 200,000 AI source citations underpin this analysis, produced by prompts specific to the retail banking industry. The AI responses from four AI models span 12 countries over the course of Q2 2026.
- Reddit climbed from #2 to #1 in the window: Its citation share more than tripled, from 3% to 8%, while YouTube fell from #1 to #8.
- 24% of ChatGPT's citations are from user-generated domains: Reddit and forums, making ChatGPT the most community-reliant model.
- 42% of Google AI Overview's citations are from commercial domains: The highest of any model, comparison and money-transfer pages dominate.
- 78% of Swedish citations are local: Local .se domains carry 78% of Swedish-prompt citations, versus just 30% for Spanish.
- ~71% of top sources differ between any two models: Any two of the four share just 29% of their top-20 cited domains.
Which sources should you target to get cited as a retail banking brand?
There is no single source list that satisfies all four models, so match the target to the model. Microsoft Copilot leans on consumer watchdogs and structured comparison sites, national consumer-protection bodies and local portals like consumentenbond.nl, which.co.uk, and rankia.com, so trade-press and watchdog coverage moves it most, and it rewards local-country domains in nearly every non-English market.
Google AI Overview and Grok converge on a spine of high-authority aggregators, youtube.com, reddit.com, forbes.com, wise.com, and nerdwallet.com, with Google AI Overview favoring commercial comparison and money-transfer pages above all. ChatGPT is the community model: with 23.8% of its citations coming from user-generated content, primarily Reddit, community reputation there is the clearest path into its answers.
How have AI source rankings changed over time in the retail banking industry?
We split the 110-day window at its midpoint and compared the most-cited domains in each half by citation share (share, not raw count, because the second half was a lower-volume slice). The ranking is far from static.
The headline mover is Reddit, whose citation share more than tripled to claim the #1 spot while YouTube fell from first to eighth, and comparison portals finder.com and finder.com.au climbed sharply. Treat the direction as solid and the magnitude as indicative. AI citation rankings are dynamic, not static, track them in the live AI visibility rankings.
What type of content do AI models cite for retail banks?
The models differ not just on which domains but on what type of content they trust. We classified every cited domain into content categories. Editorial and commercial sources lead everywhere, but the secondary preferences diverge sharply.
Three tells stand out. Microsoft Copilot is the most editorial-heavy model (47.6%) and the heaviest user of reference material (10.7%), consistent with its lean toward watchdogs and structured comparison sites. Google AI Overview is the most commercial (41.6%), pulling toward vendor and money-comparison pages. And ChatGPT is the most community-driven, with 23.8% of its citations coming from user-generated content, primarily Reddit. Trade-press placements move Microsoft Copilot, comparison-site presence moves Google AI Overview, and community reputation on Reddit moves ChatGPT.
Do AI models cite local-language content for retail banks?
Outside English-speaking markets, models vary sharply in how often they cite local-country domains. Using country-code top-level domains as a proxy for local-language sourcing, the local-domain citation rate ranges from 77.5% (Swedish) down to 29.9% (Spanish). English prompts are excluded, English content overwhelmingly lives on generic domains.
Smaller-market languages (Swedish, Dutch, German) pull heavily on home-country domains, local banks, regulators, and comparison sites dominate. Spanish is the outlier at 29.9%, but its prompts span three markets (Spain, Mexico, Argentina) and much Spanish banking content lives on .com domains the proxy counts as non-local, so read that figure as a floor.
Which AI model relies most on local sources for retail banks?
The localization gap between models is large and consistent. Microsoft Copilot cites local-domain sources far more often than Grok in nearly every language tested.
Microsoft Copilot leads localization in five of six languages, often by 15–25 points over Grok and ChatGPT in the same market. Google AI Overview shows no French-language responses over the window, a data-collection gap, not a behavioral signal, and the reason its French cell is blank. For a bank in a smaller-language market, being cited locally matters far more inside Microsoft Copilot than inside Grok, which will happily answer a Dutch banking prompt with a .com source.
Should retail banks optimize for each AI model separately?
Yes, almost entirely. When the four models answer the same retail banking questions, their top-cited domains barely converge. We compared the 20 most-cited domains for each model and measured how much each pair shares.
Google AI Overview and Grok converge on a shared spine of high-authority aggregators, youtube.com, reddit.com, forbes.com, wise.com, nerdwallet.com, while Microsoft Copilot stands apart, anchoring on national consumer-protection bodies and local comparison portals like consumentenbond.nl, which.co.uk, and rankia.com. A bank visible on one model can be absent from roughly 71% of the domains another model prefers.
How many sources does each AI model cite for retail banks?
The models don't just disagree on which sources, they disagree on how many. Grok casts a very wide net; Microsoft Copilot answers from a tight handful.
Grok cites roughly 26 sources per answer, about 3.5 times as many as Microsoft Copilot. Getting cited by Grok means competing in a crowd of around 26 sources, while a citation from Microsoft Copilot, which cites about 7, carries far more weight per placement.
Context
This analysis draws from Temso's AI visibility monitoring platform, which tracks how brands appear in AI model responses across ChatGPT, Microsoft Copilot, Grok, and Google AI Overview. The dataset covers retail banking prompts, the questions consumers ask when choosing or comparing a bank, across 12 countries (US, GB, CA, AU, DE, FR, IT, NL, SE, ES, MX, AR) and seven languages over roughly sixteen weeks (10 March – 29 June 2026).
It measures what AI models cite, not which banks they recommend or how they rank them. These findings reflect citation behavior for retail banking prompts in the monitored markets, and may not generalize to all institutions, prompt types, or other industry verticals. One coverage gap is worth naming: Google AI Overview returned no French-language responses in this window, so its French behavior is unobserved.
Methodology
How we measured this
We tracked four AI models responding to retail banking prompts in local languages across 12 countries. Each response was parsed to extract source citations: the URLs, domains, and metadata referenced. Domain categories (editorial, commercial, UGC, reference, institutional) were assigned from a global domain registry. Cross-model overlap was measured using Jaccard similarity on each model pair's top-20 most-cited domains, with a two-proportion z-test confirming the most- versus least-overlapping pairs differ significantly (p = 0.0075). Temporal analysis split the observation period at its midpoint and compared domain rankings by citation share in each half. Model coverage varied across the observation window, so temporal movements are reported as relative ranks within each half.
The analysis covers over 200,000 cited sources from 21,133 AI responses. Sample sizes exceeded recommended thresholds for every reported finding (smallest model, ChatGPT, n = over 20,000 cited sources). Localization is measured by a country-code-domain proxy, so those figures understate true local-language sourcing, local-language content on .com domains counts as non-local, which most affects Spanish, and they exclude English-language prompts, which sit overwhelmingly on generic domains.
Frequently asked questions
Do different AI models cite the same banking sources?
No, barely. Any two of the four models share only about 29% of their top-cited domains on average, so roughly 71% of what one model relies on is absent from another's top-20. There is no single "AI search" to optimize for in retail banking.
Which AI model cites the most sources per answer?
Grok, by a wide margin, about 26 cited sources per answer, versus 9.5 for Google AI Overview, 7.4 for Microsoft Copilot, and 6.3 for ChatGPT. Grok casts a far wider net; ChatGPT and Microsoft Copilot answer from a tight handful.
Which AI model favors local-language sources for banks?
Microsoft Copilot, consistently. It cites the most local-domain content in five of six non-English languages, leading Grok and ChatGPT by 15–25 points in markets like Germany, Sweden, and the Netherlands. Grok and ChatGPT lean more on global .com sources even for local-language prompts.
Why is the Spanish localization rate so low?
Partly measurement. Spanish prompts span Spain, Mexico, and Argentina, and a lot of Spanish banking content lives on .com domains like helpmycash.com and rankia.com that our local-domain measure doesn't credit. The 29.9% figure is a floor; the real local-language share is higher.
What type of content should a bank aim to appear in?
It depends on the model. Microsoft Copilot is editorial-heavy (47.6%) and rewards trade-press and consumer-watchdog coverage; Google AI Overview is the most commercial (41.6%) and favors comparison sites; ChatGPT pulls 23.8% of its citations from user-generated content, chiefly Reddit. A single tactic won't cover all three.
Did the most-cited banking sources change over the period?
Yes. Reddit's citation share more than tripled to take the #1 spot while YouTube fell from first to eighth, and comparison portals finder.com and finder.com.au climbed sharply. We read the direction as solid and the magnitude as indicative.
Does being cited mean the AI is recommending my bank?
No. This data tracks which web pages a model referenced, not which banks it endorsed or how it ranked them. A domain can be cited because it criticizes, compares, or merely mentions a brand. Citation presence is about visibility, not approval.
