政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/124741
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  全文笔数/总笔数 : 113311/144292 (79%)
造访人次 : 50937650      在线人数 : 923
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜寻范围 查询小技巧：
  • 您可在西文检索词汇前后加上"双引号"，以获取较精准的检索结果
  • 若欲以作者姓名搜寻，建议至进阶搜寻限定作者字段，可获得较完整数据
    •  进阶搜寻
    政大機構典藏 > 商學院 > 金融學系 > 學位論文 >  Item 140.119/124741


    请使用永久网址来引用或连结此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/124741


    题名: 基於隨機森林模型下P2P網路借貸違約預測
    The prediction of default in P2P Lending based on Random Forest Model
    作者: 吳志龍
    Wu, Zhi-Long
    贡献者: 廖四郎
    Liao, Szu-Lang
    吳志龍
    Wu, Zhi-Long
    关键词: P2P借貸
    隨機森林模型
    Logistic回歸模型
    個人信用風險評估
    P2P Lending
    Random Forest
    Logistic regreesion
    Private credit risk evaluation
    日期: 2019
    上传时间: 2019-08-07 16:13:06 (UTC+8)
    摘要: 摘要
    本研究使用傳統的Logistic回歸模型與機器學習的隨機森林模型對P2P借貸的個人信用風險進行評估預測。本研究的數據來源於LendingClub的2018年度公開數據資料，先對P2P借貸的個人信用風險因素進行挑選，再使用挑選出的變量對Logistic回歸模型與隨機森林模型進行訓練，並用測試集檢驗兩個模型對個人信用風險的預測能力。結果表明，隨機森林模型的在決策樹為800棵，每棵決策樹的特征值為3個的時候，隨機森林模型預測準確率最高。與Logistic回歸模型比較，隨機森林模型有著更高的精度。本研究還對兩個模型進行了模型性能的比較，結果表明隨機森林的模型性能好過去Logistic回歸模型。

    關鍵詞：P2P借貸、隨機森林模型、Logistic回歸模型、個人信用風險評估
    Abstract
    In this paper we evaluate and predict the private credit risk in P2P lending by using traditional Logistic regression and Random Forest in machine learning. For the open data from LendingClub in 2018, we select the private credit risk factors of P2P lending first, and train the Logistic regression and Random Forest model with selected variables. We test the prediction ability of two models with test set. The result shows that when there are 800 decision trees and 3 features for each tree in Random Forest model, accuracy of the model reaches best. Compared with Logistic regression, Random Forest has higher precision. We also compare the performance of two models, which shows that Random Forest is better than Logistic regression.

    Keywords: P2P Lending, Random Forest, Logistic Regression, Private Credit Risk Evaluation
    參考文獻: Bekhet,H.A.,Eletter,S.F.K.(2014).Credit risk assessment model for Jordanian commercial banks: Neural scoring approach. Review of Development Finance, Vol.4,20-28.
    Berkson,J.(1944). Application of the Logistic Function to Bio-Assay. Journal of the American Statistical Association , Vol.39, 357-365.
    Breiman,L.(2001). Random forest. Machine learning, 45(1), 5-32
    Bruett,T.(2007).Cows, Kiva, and Prosper. Com: how disintermediation and the Inter net are changing microfinance. Community Development Investment Review, 2, 44-50.
    Caemichael,D.(2014). Modeling default for peer-to-peer loans . Working Paper.
    Coffman,J.Y.(1986). The proper role of tree analysis in forecasting the risk behavior of borrowers. Management Decision System, No.3, 47-59.
    Dasarathy,B.V. Sheela,B.V.(1979). A composite classifier system design: Concepts and methodology. Proceedings of the IEEE, 67(5),708-713.
    Emekter,R.Tu,Y.Jirasakuldech,B&Lu,M.(2015).Evaluating credit risk and loan performance in online Peer-to-Peer(P2P) lending. Applied Economics, 47(1), 54-70
    Everett,C.R.(2015).Group membership, relationship banking and loan default risk : the case of online social lending. Banking and Fiance Review,7(2),14-54.
    Freedman,S.Jin,G.Z.(2008).Dynamic Learning and Selection: the Early Years. University of Maryland.
    Garman,S.R.Hampshire,R.C.Krishnan,R.(2008).Person-to-Person Lending: The Pursuit of (More) Competitive Credit Markets. E-Life: Web-Enabled Convergence of Commerce, Vol.14,54-58
    Herzenstein,M.Andrews,R.L. Dholakia,U.M.Lyandres,E.(2008). The democratization of personal consumer loans Determinants of success in online peer-to-peer lending communities. Boston University School of Management Research Paper.
    Jin,G.Z.Freedman,S.(2008). Do Social Networks Solve Information Problem for Peer-to-Peer Lending? Evidence from Prosper.Com.NET Institute Working Paper, 8-43
    Klafft,M.(2008).Peer to peer lending: auctioning microcredits over the internet. Working Paper.
    Maddala,G.S.(1983).Limited-dependent and qualitative variables in econometrics. Cambridge University Press.
    Magee,J.R.(2011).Peer-to-peer lending in the United States: surviving after Dodd-Frank. North Carolina Banking Institute Journal, Vol.15, 139-174
    Makowski,P.(1985). Credit scoring branches out. Credit World,Vol.75, 30-37.
    Mateescu,A.(2015).Peer-to-Peer Lending. Data&Society,1-23.
    Iyer,R.Khwaja,A.I.Luttmer,E.F.P.&Shue,K.(2009). Screening in new credit market: Can individual lenders infer borrower creditworthiness in peer-to-peer lending?. Working Paper
    Ohlson,J.A.(1980). Financial ratios and the probabilistic prediction of bankruptcy. Journal of accounting research, Vol.18,No.1,109-131.
    Pope, Sydnor,2011.What’s in a picture, vidence of discrimination from Prosper.com. Journal of Human Resource,Vol.46,No.1, 53-92
    Serrano-cinca,C.Gutierrez-Nieto,B.&Lopez-Palacios,L.(2015).Determinants of default in P2P lending. PloS one, 10(10),e0139427
    Stiglitz,J.E.Weiss,A.(1981). Credit rationing in markets with imperfect information. The American economic review, 71(3), 393-410
    王磊、范超、解明明(2014)。數據挖掘模型在小企業主信用評分領域的應用，統計研究，31卷，第10期，89-98。
    張培強(2011)。信用卡客戶的分類研究，生產力研究，第4期， 87-88。
    張萬軍(2015)。基於大數據的個人信用風險評估模型研究，對外經濟貿易大學。
    彭康(2018)。基於P2P網絡借貸的個人信用風險評估，暨南大學。
    蘇杭西子(2018)。基於隨機森林模型的個人信用風險評估研究，湖南大學。
    劉暢(2015)。基於Logistic的P2P網絡借貸信用風險測度研究，安徽財經大學。
    描述: 碩士
    國立政治大學
    金融學系
    106352043
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0106352043
    数据类型: thesis
    DOI: 10.6814/NCCU201900322
    显示于类别:[金融學系] 學位論文

    文件中的档案:

    档案 大小格式浏览次数
    204301.pdf1076KbAdobe PDF20检视/开启


    在政大典藏中所有的数据项都受到原著作权保护.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回馈