Credit Decision System of Small and Medium Sized Micro Enterprises Based on Big Data Technology and Risk Assessment Thinking

被引:1
|
作者
Xu, Chenheng [1 ]
Tao, Jindian [1 ]
Xu, Pengyuan [2 ]
机构
[1] Tianjin Univ Commerce, Econ Coll, Tianjin 300134, Peoples R China
[2] Jiangsu Normal Univ, Jingwen Coll, Xuzhou 221116, Jiangsu, Peoples R China
来源
2021 6TH INTERNATIONAL CONFERENCE ON SMART GRID AND ELECTRICAL AUTOMATION (ICSGEA 2021) | 2021年
关键词
Decision-making Problems; Credit Risk; Comprehensive Evaluation Model; Cluster Analysis; Analytic Hierarchy Process;
D O I
10.1109/ICSGEA53208.2021.00114
中图分类号
学科分类号
摘要
In order to solve the common credit decision-making problem of most small and medium-sized enterprises, this paper proposes a new credit decision-making system for small and medium-sized enterprises based on big data technology and risk assessment thinking. The decision-making system fully analyzes the problems existing in the credit decision-making of most small and medium-sized micro enterprises, and gives full play to the powerful function of big data technology in data processing. Based on this, the decision-making system also constructs a comprehensive evaluation model, cluster analysis model, adds matlab algorithm, and from the perspective of risk assessment thinking, insists on minimizing the risk of credit decision-making. The results show that the decision-making system can analyze the credit problems of most small and medium-sized enterprises from a comprehensive and scientific perspective, and obtain the optimal credit strategy of enterprises through qualitative and quantitative analysis.
引用
收藏
页码:477 / 480
页数:4
相关论文
共 14 条
  • [1] Credit Risk Early Warning of Small and Medium-Sized Enterprises Based on Blockchain Trusted Data
    Tong, Shekun
    Zhang, Ting
    Zhang, Zhigang
    JOURNAL OF INFORMATION & KNOWLEDGE MANAGEMENT, 2022, 21 (02)
  • [2] The Correlation between Small and Medium-Sized Enterprises' Trade Credit Level and Credit Risk
    Shi JianPing
    Yang RuBing
    Xin, Zhou
    PROCEEDINGS OF THE TWELFTH WEST LAKE INTERNATIONAL CONFERENCE ON SMALL & MEDIUM BUSINESS (WLICSMB 2010), 2011, : 274 - 280
  • [3] The Research on Credit Risk Evaluation of Small and Medium-Sized Enterprises Based on DEA/AHP
    Li Jianbo
    Chen Jiajie
    ENTERPRISE GROWS IN SUSTAINING EFFICIENCY AND EFFECTIVENESS, CONFERENCE PROCEEDINGS, 2009, : 395 - 399
  • [4] An Intelligent Decision Support System for Assessing the Default Risk in Small and Medium-Sized Enterprises
    Manjarres, Diana
    Landa-Torres, Itziar
    Andonegui, Imanol
    ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, ICAISC 2017, PT II, 2017, 10246 : 533 - 542
  • [5] The Credit Risk Prediction of the Small and Medium-Sized Enterprises based on GA-v-SVR
    Wang, Wei
    Liu, Xiangdong
    Chen, Si
    2013 INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND CLOUD COMPUTING (ISCC), 2014, : 99 - 105
  • [6] Fuzzy Comprehensive Evaluation of Credit Risk of Small and Medium-sized Enterprises in the Credit Tracing Process
    Jun, Liang
    Qiang, Mei
    PROCEEDINGS OF THE 15TH INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT, VOLS A-C, 2008, : 947 - 950
  • [7] A credit risk model with an automatic override for innovative small and medium-sized enterprises
    Angilella, Silvia
    Mazzu, Sebastiano
    JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, 2019, 70 (10) : 1784 - 1800
  • [8] Credit Risk Assessment Model of Small and Medium-Sized Enterprise Based on Logistic Regression
    Sun, Hui
    Guo, Mingyuan
    2015 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT (IEEM), 2015, : 1714 - 1717
  • [9] Investigation of the Application of Machine Learning Algorithms in Credit Risk Assessment of Medium and Micro Enterprises
    Zhao, Yujie
    IEEE ACCESS, 2024, 12 : 152945 - 152958
  • [10] Research on the Evaluation of Supply Chain Finance Credit Risk of Small and Medium-Sized Enterprise Based on System Dynamics
    Jiang, Lin
    Su, Yueliang
    PROCEEDINGS OF THE FIRST INTERNATIONAL CONFERENCE ECONOMIC AND BUSINESS MANAGEMENT 2016, 2016, 16 : 59 - 64