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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/131033


    Title: 如何藉由信用評分模型協助融資/租賃公司車貸業務授信管理 – 以某租賃公司為例
    How Can a Credit Scoring Model Help Auto Loan Business in Finance/Leasing Companies – A Case Study of T-Leasing Company
    Authors: 梁芫銘
    Liang, Roy Yuan-Ming
    Contributors: 吳文傑
    Wu, Jack
    梁芫銘
    Liang, Roy Yuan-Ming
    Keywords: 信用評分
    汽車信貸
    邏輯迴歸
    金融/租賃公司
    Credit Scoring
    Auto Loan
    Logistic Regression
    Finance/Leasing Companies
    Date: 2020
    Issue Date: 2020-08-03 17:45:31 (UTC+8)
    Abstract: The aim of this study attempts to introduce how a credit scoring model can be used to help finance/leasing companies manage and reinforce their auto loan approval process. Credit scoring models are most frequently applied methods adopted by banks when evaluating loan applications. This is a data-driven approach and it is built by using historical data and statistical techniques to identify the possibility that the failure by borrowers to make repayments in accordance with the term of a loan. Finance/leasing companies focus on the lending business in high risk borrowers. Default risk is what finance/leasing companies have to be concerned about.
    In this study, a real data of auto loan product was used to build a credit scoring model. The logistic regression is the most common method to establish the model and the model validation was also conducted to prove the effectiveness. The paper presents a credit scoring model that provides finance/leasing companies an objective way to measure and manage the credit risk. The model has also identified the risk factors associated with measuring the credit risk. This thesis illustrated how the credit scoring model works and it is recommended financing/leasing companies should develop their own credit scoring model.
    Reference: 1. Crook, J.N., Edelman, D.B., Thomas, L.C. (2002). Credit Scoring and its Applications. Philadelphia: Siam
    2. Finlay, S. (2012). Credit Scoring, Response Modeling, and Insurance Rating: A Practical Guide to Forecasting Consumer Behavior (2nd edition). Hampshire UK: Palgrave Macmillan
    3. Guo, J.J., Meng, J.W., Shan, L., Wang, H.S. (2010).12 Lessons for Credit Rating Models. Taiwan: Taiwan Academy of Banking and Finance
    4. Hosmer Jr., D.W., Lemeshow, S., Sturdivant, R.X. (2013). Applied Logistic Regression (3rd edition). New Jersey:John Wiley & Sons, Inc.
    5. Mays, E. (2001). Handbook of Credit Scoring. Chicago: Glenlake Publishing Company
    6. Olson, D.L., Wu, D.D. (2008). Enterprise Risk Management. Canada: World Scientific Publishing Co. Pte. Ltd
    7. Shu, X. (2020). Knowledge Discovery in the Social Science: a Data Mining Approach. Oakland California: University of California
    8. Siddiqi, N. (2006). Credit Risk Scorecards: Developing and Implementing Intelligent Credit Scoring. Hoboken, New Jersy: John Wiley & Sons, Inc.
    9. Bank for International Settlements (2005), Working Paper No. 14 Studies on the Validation of Internal Rating Systems. Retrieved from: https://www.bis.org/publ/bcbs_wp14.pdf (access March 15th, 2020)
    10. Bank for International Settlements (2017), Basel III: Finalising post-crisis reforms. Retrieved from: https://www.bis.org/bcbs/publ/d424.htm (access March 7th, 2020)
    11. Chen, G.H., Chu, M.J., Huang, J.C. (2011). A research on credit rating model of leasing industry. (Master’s thesis, Ming Chuan University, Taipei, Taiwan) Retrieved from: http://oplab.im.ntu.edu.tw/csimweb/system/application/views/files/ICIM/20110082
    12. Financial Supervisory Commission, R.O.C. Taiwan (2020). How to enhance the function of Consumer Debt Relief Program and the Regulation Governing for the Improvement of Banking Business of Credit Card and Cash Card. Retrieved from: https://law.fsc.gov.tw/law/LawContent.aspx?id=FE057275&KeyWord=%e6%b6%88%e8%b2%bb%e9%87%91%e8%9e%8d%e5%82%b5%e5%8b%99%e5%8d%94%e5%95%86%e6%a9%9f%e5%88%b6 (accessed June 16th, 2020)
    13. Banking Bureau (2020). Banking Statistics. Retrieved from: https://www.banking.gov.tw/ch/home.jsp?id=595&parentpath=0,590 (accessed June 10th, 2020)
    14. Chailease Holding (2019). Annual Report 2018-2019。Retrieved from: http://www.chaileaseholding.com/ImgChaileaseHolding/20200519183251.pdf , (accessed April 10th, 2020)
    15. Ding, J.J. (2004).Study of Consumer Credit Risk - Introduction to Credit Scoring. Retrieved from: https://member.jcic.org.tw/main_member/fileRename.aspx?fid=298&kid=1 (accessed June 10th, 2020)
    16. Lai, B.Z. (2006). The Current Development Status of Consumer Credit Scoring System. Retrieved from: https://member.jcic.org.tw/main_member/fileRename.aspx?fid=378&kid=1 (accessed June 10th, 2020)
    17. Lai, B.Z., Tsai, R.M. (August, 2009). Consumer Credit Scoring System Product (J10) the Use in the Approval Process of Credit Card. Retrieved from: https://www.google.com/url?client=internal-element-cse&cx=010192925252739662080:8bojmtikgsc&q=https://www.jcic.org.tw/main_ch/fileRename/fileRename.aspx%3Ffid%3D631%26kid%3D1&sa=U&ved=2ahUKEwjO-J7F2_boAhUpxYsBHX_1CJI4FBAWMAV6BAgFEAI&usg=AOvVaw33ZTMH_-AyymIcZrTQJwDr (accessed March 20th, 2020)
    18. Liu, M.H., Wu, C.L. (July 24th, 2015). Reach an agreement of giving the permission to the financing and leasing companies of non-JCIC members to apply for credit reports on behalf of consumers. Retrieved from: https://www.ndc.gov.tw/News_Content.aspx?n=114AAE178CD95D4C&sms=DF717169EA26F1A3&s=15214408D3578A59 (accessed December 10th, 2019)
    Description: 碩士
    國立政治大學
    國際經營管理英語碩士學位學程(IMBA)
    102933014
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0102933014
    Data Type: thesis
    DOI: 10.6814/NCCU202000865
    Appears in Collections:[國際經營管理英語碩士學程IMBA] 學位論文

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