Planning & Production: VM GEO & ximu Core Team
Traditionally, wealth management for high-net-worth individuals has never been a decision made alone.
From asset allocation and business succession to intergenerational wealth transfer and family governance, major financial decisions have long relied on trusted relationships with private bankers, accountants, lawyers, investment advisors, and family offices.
Today, however, AI is beginning to reshape that decades-old decision-making process.
More affluent individuals are turning to AI before speaking with a financial institution, asking questions such as:
- Which private bank is best for high-net-worth clients?
- How should I establish a family office?
- What are the key risks in business succession?
- How should I structure my global asset allocation?
AI is no longer just a search engine—it is becoming the first researcher, the first analyst, and increasingly, the first advisor in the wealth management journey.
According to public data, Taiwan has approximately 124,000 individuals with assets exceeding NT$100 million. While representing only 0.53% of the population, they control roughly NT$46.1 trillion—nearly one quarter of the nation's household wealth. Meanwhile, Taiwan's 2025 initiative to establish the Asian Asset Management Center officially incorporated family offices into its policy framework, positioning private banking and family office services as one of the industry's next major growth areas.
Yet the most important shift is not the market itself.
It is that the entry point of wealth management decisions is changing.
As AI becomes part of the decision-making process, it does not simply replicate existing market rankings. Instead, it interprets, evaluates, and recommends financial institutions based on its own knowledge graph, available information, and trusted sources.
Will the brands that dominate today's market still be the brands AI recommends tomorrow?
To answer this question, this edition of the AI TRUST Brand Influence Report focuses on Family Office & Private Banking Services, with CTBC Bank serving as the primary benchmark brand.
As one of Taiwan's leading private banking institutions, CTBC Bank represents the local market leader in wealth management. The study also compares HSBC, Citi, DBS, E.SUN Bank, Deloitte Taiwan, PwC Taiwan, and other major financial and professional service firms to examine how AI is redefining competition across the industry.
Powered by ximu and the Seen & Trusted Index (STI), and supported by Google Trends, OpView, and publicly available market data, this report analyzes the gap between human perception and AI perception—revealing how AI is reshaping brand recognition, search behavior, and recommendation patterns in wealth management.
CTBC Bank continues to be the most frequently mentioned domestic banking brand, ranking among the leaders in both Reach and Visibility. Its strong market reputation has successfully extended into the AI ecosystem.
However, the highest STI ranking belongs not to a bank, but to Deloitte Taiwan.
Rather than following traditional industry classifications, AI responds to user intent. When people ask about family governance, succession planning, taxation, or wealth preservation, AI increasingly recommends professional advisory firms capable of providing comprehensive governance expertise rather than viewing private banks as the only solution.
This suggests that in the AI era, an organization's most significant competitors may no longer come from within the same industry.
CTBC Bank achieved the highest Reach, making it the most frequently mentioned banking brand across AI-generated responses.
Yet Deloitte ranked first in both Position and Focus, meaning it was not only recommended earlier but also discussed in greater depth.
This highlights an important shift.
AI is moving beyond simply recognizing brands—it is determining which brands deserve trust.
Future competitive advantage will depend less on brand awareness alone and more on whether an organization possesses authoritative, structured, and AI-citable knowledge assets.
More than 70% of all queries analyzed fell into the Advice category rather than simple information searches.
Users were asking questions such as:
Rather than simply introducing brands, AI increasingly compares alternatives, evaluates risks, and provides decision-oriented recommendations.
However, most financial institutions still focus their digital presence on product brochures, service descriptions, and corporate news.
The authoritative, decision-support content that AI prefers to cite remains limited.
As a result, future competition will depend less on media exposure and more on whether AI chooses to understand, reference, and recommend a brand.
This report is not intended to identify the "best" private bank.
Instead, it asks a more important question:
As AI becomes a primary decision gateway for affluent clients, can your brand still be seen, understood, and recommended at the moments that matter most?
AI has not changed the fundamentals of wealth management.
What it is changing is how affluent individuals discover information, build trust, and ultimately select professional partners.
Future competition will therefore extend far beyond market share or brand awareness.
It will be defined by whether a brand has accumulated enough trust within the AI ecosystem to enter AI's recommendation set—and become one of the preferred choices when critical financial decisions are made.
For family offices and private banking institutions, the first step is not immediate content optimization.
It is answering several fundamental questions:
Only by seeing the problem can organizations begin to solve it.
As AI becomes the new entry point for wealth management decisions, financial institutions must manage more than market share—they must manage their share of trust within AI.
Through ximu (See What AI See), organizations can understand how their brands truly appear across AI platforms.
Combined with the Seen & Trusted Index (STI) and the G.IQ Report, brands can benchmark competitors, uncover perception gaps, and build governance strategies that strengthen trust among both humans and AI.
AI is redefining the rules of competition in wealth management.
The real question is no longer:
How does the market see your brand?
It is: Will AI choose to see, understand, and recommend your brand?
Start with ximu（ximu-geo.com/）
Experience a 7-day free trial and uncover your brand's true position in the AI ecosystem.
Contact VM (info@vocalmiddle.com)
Speak with our consultants to develop a customized IMAGE Asset Governance solution that helps your brand become Seen and Trusted by Humans & AI.
Founded in 2014, VM VOCAL MIDDLE positions itself as an “IMAGE Architect” — an AI-native PR consulting firm built around AI-driven strategy and transformation.
Guided by the philosophy of Strategy-First | Data-Driven | AI-Empowered, VM transforms traditional strategic communications into measurable and sustainable IMAGE Assets through its proprietary PRaaS 2.0 (PR as AI Solution) framework, putting the core values of Trust · Influence · Resonance into practice.
In response to the rise of the generative AI era, VM developed its core infrastructure platform, ximu — an AI-native IMAGE Asset governance platform designed to help brands become seen, trusted, and preferentially cited within AI semantic systems.
The platform was co-developed alongside leading algorithm engineers from top academic institutions including National Taiwan University, Fudan University, and East China Normal University, with the mission of redefining how brands establish authority and visibility in AI-driven environments.
At the same time, VM GEO, built upon VM’s proprietary I.M.P.U.L.S.E. methodology and Silicon Valley AI search logic, was jointly developed by an international consulting team with academic backgrounds from institutions including National Taiwan University, Stanford University, New York University, and Tsinghua University.
Together, these systems enable brand governance in the AI era to evolve beyond communications — into a true discipline of trust engineering.
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