For two decades, choosing a financial institution depended almost exclusively on traditional search engines: the user entered a query, reviewed a list of ten links, and made a decision. Today, AI-based conversational assistants (such as ChatGPT or Gemini) have radically altered the rules of the game by delivering direct, written recommendations limited to a handful of options.
To analyze this phenomenon, Centria Group, in collaboration with an international consortium of nine institutions from five countries, has developed a groundbreaking diagnostic based on 320 real queries in ChatGPT and Gemini, cross-referenced with the public registry of the Superintendency of Banks.
Access the complete original study at Centria Group - Panamanian Banking Faces Artificial Intelligence.
The paradigm shift: From traditional SEO to GEO (Generative Engine Optimization)
The rise of language models (LLMs) introduces a change of a fundamentally different nature than classic organic ranking. While a traditional search engine acts as a neutral intermediary that leaves the decision to the user, a generative assistant selects, summarizes, and recommends.
Visibility is binary: Whoever doesn't appear in the assistant's response isn't competing at a disadvantage; they simply don't exist for the user.
The surface area narrows: There's no second page or infinite scrolling; only three or four main names fit.
Lack of internal metrics: Most financial institutions manage detailed web traffic dashboards, but operate completely blind to what AI says about their brand.
To fill this gap, GEO (Generative Engine Optimization) was born, the emerging discipline responsible for optimizing brand presence within responses generated by artificial intelligence systems.
Who leads AI recommendations in Panamanian banking?
The report's data show that the distribution of mentions is extremely uneven. Six financial institutions capture nearly three-quarters of all recommendations in the sector.
Absolute dominance of the major players
Banco General: Tops the ranking with a 97.5% presence (96% in ChatGPT and 99% in Gemini), tending to occupy the top position and sustaining its authority through its own web domain.
The Top 6: Along with Banco General, institutions such as BAC (78.4%), Banistmo (71.6%), Banco Nacional de Panamá (64.7%), Caja de Ahorros (61.6%) and Global Bank (59.7%) together account for 73% of total mentions.
The sharp drop-off: From the seventh position onward, the presence of the remaining institutions falls drastically below 24%, becoming occasional appearances.
The importance of intent: The question decides who exists
A key finding of the Centria Group study is that thirteen licensed banks appeared invisible in general queries. However, when introducing specific product queries, specialized institutions emerged with dominant strength in their niches:
Prival Bank: Reaches 90% visibility in private banking.
Bladex: Jumps to 90% in foreign trade.
Citibank: Dominates with 90% in corporate banking.
Pacific Bank: Stands out with 80% in fixed-term deposits.
Where does AI get its information about banks?
Understanding the behavior of generative engines requires analyzing their information sources. The study reveals two radically opposed philosophies between the leading assistants:
ChatGPT (Institutional Model): 82% of its citations come from official bank websites and the regulator's portal (Superintendency of Banks), with the latter being its most referenced source.
Gemini (Open Ecosystem Model): Two-thirds of its citations correspond to news media, forums, and social networks. Its most-cited individual source is Reddit, far surpassing the website of any banking institution.
This phenomenon creates notable paradoxes, such as the case of Banistmo, which registers a 76% appearance rate in Gemini's responses, yet whose official website is cited in barely 6% of them. This demonstrates that AI visibility is built mainly in third-party spaces (reviews, forums, and media outlets), beyond the corporate website.
Critical risks: Outdated information and algorithmic variability
The Centria Group report warns of two critical operational vulnerabilities for financial brands:
Risk of outdated data: Institutions undergoing liquidation or voluntary absorption approved by the regulator continue to be actively recommended by AI for products they no longer offer. Language models process official historical documents and mistakenly reinterpret them in the present tense.
Visibility as probability, not position: Repeating an identical query five times within the same session yields significant variations; two responses to the same question share only between 58% and 61% of the brands mentioned. In AI, there are no static positions, only probabilities of appearance.
Key strategies for banking in the age of AI
To compete successfully in this new GEO environment, financial institutions must adopt approaches tailored to their size and objectives:
Leading institutions: Should maintain an active defensive posture, implementing periodic measurements and auditing the accuracy of the data circulating about their brand.
Mid-sized banks: Need to evaluate critical differences in recommendations between different assistants (for example, the visibility mismatch between ChatGPT and Gemini) to avoid optimizing blindly.
Specialized banks: Their realistic goal isn't to compete for generic recommendations (dominated by the major players), but to secure and dominate the specific conversation around their product or segment.
Frequently Asked Questions (FAQs) about Panamanian banking and Artificial Intelligence
What is GEO (Generative Engine Optimization) in the banking sector?
GEO is the evolution of traditional SEO focused on optimizing a brand's visibility and reputation within responses written by artificial intelligence assistants (such as ChatGPT and Gemini), where traditional lists of links disappear in favor of direct recommendations.
Why does AI almost always recommend the same banks in Panama?
Due to the high concentration of mentions: six financial institutions (led by Banco General) capture 73% of AI's general recommendations, driven by strong brand recognition and robust indexing of institutional and third-party content.
How can a mid-sized or specialized bank improve its visibility with AI?
Through a strategy focused on product and niche queries (such as private banking, foreign trade, or mortgages), actively managing its reputation across external sources (media, forums, and comparison sites) that feed the assistants' algorithms.
How reliable is the information AI provides about banks in Panama?
The study demonstrates that there is a real risk of outdated information. AI assistants can end up recommending institutions that are undergoing liquidation or merger processes by mistakenly interpreting historical regulatory filings as if they were operating in the present.
To dive deeper into the detailed metrics by institution, comparative tables, and full methodology, check out the original document at Centria Group - Panamanian Banking Faces Artificial Intelligence.
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