政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/150077
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113311/144292 (79%)
Visitors : 50938956      Online Users : 991
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
    •  Adv. Search
    Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer Goto mobile version


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/150077


    Title: 銀行業對中小企業授信業務策略及風險評估之探討
    A STUDY OF CREDIT BUSINESS STRATEGY AND RISK ASSESSMENT FOR SMALL AND MEDIUM ENTERPRISES IN THE BANKING INDUSTRY.
    Authors: 洪梓育
    Hung, Tzu-Yu
    Contributors: 張士傑
    Chang, Shih-Chieh
    洪梓育
    Hung, Tzu-Yu
    Keywords: 銀行業
    中小企業
    授信業務策略
    風險評估
    信用評分模型
    財務評估
    Date: 2024
    Issue Date: 2024-03-01 11:52:57 (UTC+8)
    Abstract: 本論文旨在深入研究銀行業對中小企業授信業務策略和相應風險評估方法。中小企業在全球經濟中扮演著關鍵角色，對就業機會和經濟增長亦不可或缺。在回顧過往文獻，首先分析銀行業對中小企業授信業務的重要性，強調授信業務對中小企業經營和成長有密不可分的關係。接著深入研究銀行業授信策略的演變，過去銀行主要依賴傳統的財務評估和人工審核，但隨著數據科技的革新，現代銀行業採用更智能化方法來評估風險和提高授信效率。後續章節專注於銀行業對中小企業授信策略的具體探討，詳細描述貸款申請審核流程，強調高效率、客製化的申請架構，提高中小企業貸款成功率。此外分析銀行擔保要求與彈性，並強調在風險控制前提下，為企業提供多樣化選擇。在風險評估部分，探討銀行業對中小企業風險評估方法的演進，從傳統的財務評估，到引入信用評分模型和綜合性風險評估，指出了不同方法的優點和局限性。
    綜合研究結果，本論文得出以下結論：銀行業對中小企業授信業務策略應當持續創新和改進，採用更智能化的技術與方法，滿足中小企業融資需求。同時，風險評估應注重全方位資訊融合，並運用數據科技提高評估的準確性及效率。
    Reference: 1. 中小企業白皮書，2022年
    2. 台灣金融研訓院課程講義，2018年
    3. 王凱與張曉春等（2019）《銀行授信業務對中小企業創新的影響研究》
    4. 王大成與陳小玲（2021）《銀行授信業務對中小企業國際化的影響研究》
    5. 王建國與劉偉（2021）《數據科學在銀行授信業務中的應用研究》
    6. 王莉與李建國（2021）《數據科學在銀行授信中的應用與效果研究》
    7. 王靜與周明（2022）《數據驅動的銀行授信策略對中小企業融資的影響研究》
    8. 王靜與李偉（2021）《大數據技術在銀行授信業務中的應用與展望》
    9. 王偉與陳靜（2021）《基於大數據技術的銀行授信業務創新與發展》
    10. 田立華與李小明（2022）《人工智能在銀行授信中的應用與展望》
    11. 李娟（2021）,《銀行授信業務對中小企業成長的影響研究》
    12. 李小雲與陳建民（2022）《銀行授信業務對中小企業可持續發展的影響研究》
    13. 李娜與黃文華（2021）《數據的銀行授信風險管理研究》
    14. 李明與劉偉（2021）《基於大數據的銀行授信策略優化研究》
    15. 李華與陳曉（2021）《數據科學在中小企業授信中的應用分析》
    16. 李靜與許芳（2022）《數據驅動的銀行授信策略對金融風險的影響研究》
    17. 李偉與趙華（2022）《大數據與人工智能在銀行授信業務中的綜合應用分析》
    18. 吳琪與林文豪（2021）《銀行授信業務對中小企業社會責任履行的影響研究》
    19. 林志勇與陳建明（2020）《銀行授信業務對中小企業業務多樣化的影響研究》
    20. 周佳佳與蔡明宇（2021）《銀行授信業務對中小企業創業動力的影響研究》
    21. 胡偉與張小明（2021）《數據驅動的銀行授信策略與中小企業發展的關係研究》
    22. 袁立與陳燕（2022）《基於人工智能的銀行授信模型優化研究》
    23. 陳思琪與劉海濤（2022）《銀行授信業務對中小企業就業影響研究》
    24. 陳曉與趙靜（2022）《大數據技術在銀行授信中的應用與效果分析》
    25. 陳華與張偉（2022）《數據科學技術在銀行授信業務中的應用與展望》
    26. 陳靜與劉華（2021）《人工智能在銀行授信業務中的應用與展望》
    27. 許明達與劉佳（2023）《銀行授信業務對中小企業金融風險的影響研究》
    28. 張曉明與劉華（2020）《數據驅動的銀行授信策略研究》
    29. 趙偉與劉靜（2022）《數據科學與銀行中小企業授信業務創新研究》
    30. 楊霖與賴曉春（2020）《銀行授信業務對中小企業融資影響研究》
    網際網路
    31. 家數及銷售額整理自財政部財政資訊中心，營業稅徵收統計原始資料，2020-2021年
    32. 就業及受僱人數資料整理自行政院主計總處，人力資源調查統計原始資料，2020-2021年
    33. 各國中小企業定義
    台灣資料:台灣宗和研究院https://www.tri.org.tw/ceo/
    美國資料: https://hdl.handle.net/11296/q6p9as
    英國資料: https://www.newton.com.tw/wiki/%E4%B8%AD%E5%B0%8F%E4%BC%81%E6%A5%AD
    日本資料:日本中小企業廳https://www.chusho.meti.go.jp/soshiki/teigi.html
    歐盟資料: Recommendation 2003/361/EC: SME Definition
    中國資料:中華人民共和國工信部https://www.gov.cn/zwgk/2011-07/04/content_1898747.htm

    英文參考文獻
    34. Chaudhary, A., & Paul, A. (2019). "Bank Loan Credit Risk Assessment using Machine Learning Techniques: A Comparative Study." International Journal of Computer Applications, 182(46), 1-8.
    35. Chen, S., Zhang, H., & Wu, X. (2020). "Credit Risk Assessment of Small and Medium-Sized Enterprises Based on Rough Set Theory and Logistic Regression." 2020 2nd International Conference on Big Data and Education (ICBDE), 19-24.
    36. Chen, Z., Xue, L., & Li, Q. (2018). "Credit Risk Evaluation of Small and Medium-Sized Enterprises Based on Fuzzy Comprehensive Evaluation and Grey Correlation Analysis." 2018 IEEE International Conference on Big Data and Smart Computing (BigComp), 310-314.
    37. Fu, L., & Zhang, Y. (2020). "Application of Machine Learning Algorithm in Credit Risk Evaluation of Small and Medium-Sized Enterprises." 2020 6th International Conference on Control, Automation and Robotics (ICCAR), 395-399.
    38. Huang, J., Guo, F., & Li, Q. (2018). "Credit Risk Evaluation of Small and Medium-Sized Enterprises Based on Support Vector Machine." 2018 International Conference on Computational Science and Computational Intelligence (CSCI), 1680-1684.
    39. i, S., Cai, Y., & Wang, X. (2019). "Credit Risk Evaluation of Small and Medium-Sized Enterprises based on Data Mining Technology." 2019 5th International Conference on Computer and Technology Applications (ICCTA), 135-139.
    40. Li, C., Li, J., & Li, Y. (2019). "Credit Risk Evaluation of Small and Medium-Sized Enterprises Based on Principal Component Analysis and Support Vector Machine." 2019 3rd International Conference on Information Science and System (ICISS), 607-611.
    41. Li, J., Hu, B., & Zhang, Y. (2021). "Credit Risk Assessment of Small and Medium-Sized Enterprises Based on Deep Learning Algorithm." 2021 IEEE International Conference on Power Electronics and Energy Engineering (PEEE), 390-394.
    42. Li, Y., & Yang, J. (2019). "Research on Credit Risk Evaluation of Small and Medium-Sized Enterprises Based on Data Fusion Technology." 2019 International Conference on Communications, Information System and Computer Engineering (CISCE), 271-274.
    43. Li, Y., Tang, K., & Zhang, X. (2020). "Credit Risk Evaluation of Small and Medium-Sized Enterprises Based on Data Envelopment Analysis and Support Vector Machine." 2020 5th International Conference on Control and Robotics Engineering (ICCRE), 348-352.
    44. Liu, C., Huang, M., & Liu, J. (2021). "Credit Risk Evaluation of Small and Medium-Sized Enterprises Based on LSTM Neural Network." 2021 4th International Conference on Control and Robots (ICCR), 57-61.
    45. Liu, Y., Chen, Y., & Yang, L. (2020). "Credit Risk Assessment of Small and Medium-Sized Enterprises Based on Rough Set and Decision Tree Algorithm." 2020 9th International Conference on Industrial Technology and Management (ICITM), 75-79.
    46. Sun, Y., Zhang, H., & Huang, W. (2019). "Credit Risk Assessment of Small and Medium-Sized Enterprises Based on Improved K-Nearest Neighbor Algorithm." 2019 2nd International Conference on Artificial Intelligence and Big Data (ICAIBD), 58-63.
    47. Wang, C., Wang, S., & He, Y. (2018). "Credit Risk Assessment of Small and Medium-Sized Enterprises Based on Combination Forecasting Model." 2018 3rd International Conference on Electronics and Communication Engineering (ICECE), 83-87.
    48. Wang, H., Sun, L., & Li, P. (2021). "Credit Risk Assessment of Small and Medium-Sized Enterprises Based on Improved Particle Swarm Optimization and Grey Incidence Analysis." 2021 8th International Conference on Systems and Informatics (ICSAI), 814-819.
    49. Wang, Y., Lu, H., & Liu, W. (2020). "Credit Risk Evaluation of Small and Medium-Sized Enterprises Based on Ensemble Learning Algorithm." 2020 15th IEEE Conference on Industrial Electronics and Applications (ICIEA), 454-458.
    50. Wu, J., Qian, J., & Wu, C. (2019). "Credit Risk Evaluation of Small and Medium-Sized Enterprises Based on Grey Incidence Analysis and Random Forest." 2019 4th International Conference on Automation, Control and Robots (ICACR), 249-254.
    51. Wu, Y., Yang, L., & Zhu, Y. (2019). "Credit Risk Evaluation of Small and Medium-Sized Enterprises Based on Fuzzy Analytic Hierarchy Process and Random Forest." 2019 6th International Conference on Industrial Engineering and Applications (ICIEA), 112-116.
    52. Xie, Y., Yuan, Y., & Yu, L. (2019). "Credit Risk Evaluation of Small and Medium-Sized Enterprises Based on Improved Back Propagation Neural Network." 2019 4th International Conference on Automation, Control and Robots (ICACR), 171-175.
    53. Xu, D., Song, Q., & Yang, L. (2019). "Credit Risk Assessment of Small and Medium-Sized Enterprises Based on Improved C4.5 Decision Tree Algorithm." 2019 3rd International Conference on Computer Science and Application Engineering (CSAE), 175-179.
    54. Zhang, L., Wang, Y., & Zhang, H. (2021). "Credit Risk Evaluation of Small and Medium-Sized Enterprises Based on Bayesian Network." 2021 IEEE International Conference on Industrial Electronics and Electrical Engineering (ICIEEE), 328-333.
    55. Zhang, S., Li, H., & Zhu, J. (2019). "Credit Risk Evaluation of Small and Medium-Sized Enterprises Based on Logistic Regression Model." 2019 International Conference on Data Science and Information Technology (DSIT), 115-118.
    56. Zhou, Y., Cheng, Z., & Zhang, D. (2019). "Credit Risk Evaluation of Small and Medium-Sized Enterprises Based on Genetic Algorithm and Support Vector Machine." 2019 5th International Conference on Control, Automation and Robotics (ICCAR), 391-395.
    Description: 碩士
    國立政治大學
    經營管理碩士學程(EMBA)
    106932133
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0106932133
    Data Type: thesis
    Appears in Collections:[Executive Master of Business Administration] Theses

    Files in This Item:

    File Description SizeFormat
    213301.pdf1148KbAdobe PDF3View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    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 ©   - Feedback