博碩士論文 etd-0620117-153611 詳細資訊


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姓名 詹鳳華(Feng-Hua Chan) 電子郵件信箱 E-mail 資料不公開
畢業系所 管理學院國際經營管理碩士學程(Master of Business Administration Program in International Business)
畢業學位 碩士(Master) 畢業時期 106學年第1學期
論文名稱(中) 應用機器學習方法於貸款的違約比較與預測 - 以美國與中國為例
論文名稱(英) Machine Learning Application to Loan Default Comparison and Prediction - A case study in USA and China
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    紙本論文:5 年後公開 (2022-11-19 公開)

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    論文語文/頁數 英文/55
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    摘要(中) 網路貸款已經在西方國家ex: 美國、英國盛行很久了。全世界第一個網貸平台為英國Zopa, 致力於提供小額貸款給借款人。本研究中,我們使用機器學習的方式去預測Lending Club借款人的違約風險並且找出影響違約因素的因子。我們利用羅吉斯回歸以及隨機森林的方式進行分析。接著比較網路貸款在美國以及中國之間不一樣的地方東西方國家。
    摘要(英) Online Peer-to-Peer (P2P) lending has been prevailing in the West countries such as USA, UK. The first company to offer peer-to-peer loans in the world was Zopa in UK which provide platform for borrowers can obtain small loan from lenders. In this study, we use machine learning algorithms to predict borrowers’ default risk and discover factors that impact on the rate of loan default with example and data from LendingClub.com. We use logistic regression and random forest to do analysis and identify what is the most influential factor will affect P2P lending. Finally, we compare the difference of P2P lending market between USA and China.
    關鍵字(中)
  • 隨機森林
  • 機器學習
  • 美國
  • 中國
  • 網路貸款
  • 羅吉斯回歸
  • 關鍵字(英)
  • Random Forest
  • Logistic Regression
  • Machine Learning
  • USA
  • China
  • P2P Lending
  • 論文目次 Acknowledgement i
    摘要 ii
    Abstract iii
    Content iv
    List of Table vi
    List of Figure vii
    1. Introduction 1
    1.1. Background 1
    1.2. The study organization 2
    2. Literature Review 3
    3. Methodology 5
    3.1. Dataset Description 5
    3.2. Logistic Regression 6
    3.3. Forest Plot 13
    3.4. Random Forest 16
    3.5. PPDai’s Funding 18
    4. Discussion, Comparison, and Implication 22
    4.1. Comparative Evaluation 22
    4.2. The Risk of China P2P Platforms 23
    4.3. China P2P Platforms 27
    4.4. The new policy to solve China P2P platforms problem 30
    4.5. Compare China and USA’s P2P lending industry situation 32
    5. Conclusion 37
    6. Reference 38
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    口試委員
  • 李珮如 - 召集委員
  • 林耕霈 - 委員
  • 康藝晃 - 指導教授
  • 口試日期 2017-09-05 繳交日期 2017-11-19

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