| 研究生: |
葉恩瑜 Yeh, En-Yu |
|---|---|
| 論文名稱: |
倫巴底貸款對銀行經營效益之影響—以C銀行為例 The Impact of Lombard Lending on Bank’s Operating Performance: A Case Study of Bank C |
| 指導教授: |
顏盟峯
Yen, Meng-Feng |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 高階管理碩士在職專班(EMBA) Executive Master of Business Administration (EMBA) |
| 論文出版年: | 2026 |
| 畢業學年度: | 114 |
| 語文別: | 中文 |
| 論文頁數: | 75 |
| 中文關鍵詞: | 倫巴底貸款 、德爾菲法 、層級分析法 、經營效益 、財富管理 |
| 外文關鍵詞: | Lombard lending, operating performance, Delphi method, analytic hierarchy process, wealth management |
| 相關次數: | 點閱:3 下載:0 |
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本研究旨在探討倫巴底貸款(Lombard Lending)對銀行經營效益之影響,並以C 銀行為個案。倫巴底貸款係以客戶持有之高流動性金融資產為擔保所承作之融資,客戶無須處分既有資產即可取得流動性,已成為國際私人銀行深化客戶關係與創造收益之重要工具;惟該業務於臺灣市場仍處發展初期,銀行在風險控管與制度配套上面臨諸多挑戰,亦缺乏系統性之經營效益評估架構。
本研究先經由文獻探討與實務觀察,建構「經營效益與客戶價值」、「風險控管與內部挑戰」、「策略發展與市場展望」三大構面之初步層級架構;繼而以德爾菲法(Delphi Method)進行兩回合專家問卷,匯集銀行實務專家之共識,據以確認並修正關鍵因子;最後以層級分析法(Analytic Hierarchy Process, AHP)求算各構面與因子之相對權重,辨識影響銀行經營效益之優先順序。
研究結果顯示,兩回合德爾菲問卷後專家意見順利收斂,評估架構確立為三大構面、十五項關鍵因子,全數獲得專家共識;層級分析結果則顯示三大構面重要性相近,整體優先順序以「建立動態 LTV 量化模型」、「跨部門流程整合」與「導入 AI 即時風控系統」居前,呈現「策略優先、風險為基礎」之型態。
整體而言,倫巴底貸款對銀行經營效益之貢獻,主要在於管理資產之留存與高資產客戶關係之深化,而非短期利差收益;其推展關鍵在於將貸放成數管理由經驗判斷升級為可動態調整之量化模型,並輔以跨部門流程整合與即時風控機制。本研究所建構之評估架構與優先順序,可供銀行推動財富管理業務資源配置之參考。
Lombard lending, a form of credit collateralized by a client's portfolio of liquid financial assets, has become an important instrument for private banks to deepen client relationships and generate revenue, yet the business remains at an early stage of development in Taiwan and lacks a systematic framework for evaluating its contribution to bank operating performance. Taking Bank C as a case, this study constructs such a framework with a two-round Delphi survey of banking practitioners and derives the relative priorities of the evaluation factors with the Analytic Hierarchy Process (AHP). The finalized framework comprises three dimensions and fifteen key factors, all of which reached expert consensus. The AHP results show that the three dimensions carry similar weights, while the development of a dynamic loan-to-value (LTV) quantitative model, cross-departmental process integration, and the adoption of an AI-based real-time risk-control system rank as the top three overall priorities. The findings depict a pattern of "strategy first, risk as the foundation" and provide a practical reference for resource allocation in wealth-management banking.
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