隨著生成式AI技術的爆發性成長，台灣金融業也加快速度從「數位化」朝「智能化」前進。本次研究聚焦於大型語言模型（LLM）在高端財富管理領域的適用性評估，並進一步探討AI在面對高資產（HNW）客戶複雜且多元的需求時，是否具備與「人類專家團隊」同等或互補的專業服務能力。
本次研究以台灣財富管理標竿-中國信託銀行（CTBC）作為個案分析對象。首先，透過文獻探討HNW客戶特徵、LLM技術及金融合規；接著分析中信銀現行的全資產規劃與專家團隊協同機制。在實證研究部分，本研究設計了二組涵蓋稅務、法律、信託、保險與投資需求的真實去識別化案例進行情境測試。
AI工具則是採用 Google Gemini 3 Pro模型建構具備「中國信託專家團隊」能力的「AI專家」，並與行內專家團隊的標準答案進行對比。評估指標嚴謹涵蓋了稅務邏輯的「準確性」、風險轉嫁計畫的「完整度」、台灣銀行法與洗錢防制的「合規性」，以及模擬人類專家回應的「同理心與邏輯力」。
研究發現，AI在資訊分析與需求歸納表現優異，但在處理台灣特定法規細節及家族情感協調等層面仍有待精進。最後，本研究針對如何導入AI輔助專家團隊提出實務建議，最終達到提升銀行業財富管理服務的效率與精準度，並為人機協作模式提供結合實務經驗研究結果。

As Generative AI technology experiences explosive growth, Taiwan's financial industry is accelerating its transformation from "digitalization" to "intelligence." This study focuses on evaluating the applicability of Large Language Models (LLMs) in high-end wealth management. It explores whether AI possesses professional service capabilities that are equivalent to or complementary to "human expert teams" when facing the complex and diverse needs of High-Net-Worth (HNW) individuals.
Taking CTBC Bank, a benchmark in Taiwan's wealth management sector, as a case study, this research first examines HNW client characteristics, LLM technology, and financial compliance through a literature review. It then analyzes CTBC’s current wealth planning and expert collaboration mechanisms. For the empirical study, two de-identified real-world scenarios covering tax, legal, trust, insurance, and investment needs were designed for testing.
The AI tool utilized the Google Gemini 3 Pro model to construct an "AI Expert" mimicking the capabilities of CTBC’s professional team. The results were compared against standard answers from internal experts. Evaluation metrics strictly covered the "accuracy" of tax logic, "completeness" of risk transfer plans, "compliance" with Taiwan’s Banking Act and AML regulations, as well as "empathy and logical reasoning" in simulating human responses.
The findings indicate that while AI excels in data analysis and requirement summarization, it still needs improvement in handling specific Taiwanese regulatory details and family emotional coordination. Finally, this study provides practical recommendations on integrating AI to assist expert teams, aiming to enhance the efficiency and precision of wealth management services and provide a research foundation for human-AI collaboration.
Keywords: Wealth Management, Generative AI, Expert Team

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