An Analysis of Credit Risk Prediction for Small and Micro Enterprises

Authors

  • Wei Hu
    School of Information Resource Management, Renmin University of China, Beijing China
  • Yuhuan Wu
    School of Information Resource Management, Renmin University of China, Beijing China
  • Ziting Yang
    School of Information Resource Management, Renmin University of China, Beijing China

DOI:

https://doi.org/10.70891/JAIR.2024.110004

Keywords:

SMEs, credit risk, machine learning, data analysis

Abstract

Digital inclusive finance has emerged as a significant catalyst for the high-quality development of small and micro enterprises (SMEs). This study, grounded in credit risk prediction theory, develops a comprehensive profiling and predictive model for SMEs, offering insights into innovative mechanisms by which inclusive finance can support their sustainable growth. Utilizing an extensive literature review, along with experimental modeling based on publicly available data, the study explores two approaches to feature construction. By employing diverse algorithms, it builds predictive models and proposes tailored policy recommendations to enhance inclusive financial practices. The credit prediction model facilitates targeted financial support and innovation management strategies for SMEs, contributing a fresh perspective to advancing the quality and effectiveness of digital inclusive finance

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Published

2024-11-23

Issue

Section

Articles

How to Cite

Hu, W., Wu, Y., & Yang, Z. (2024). An Analysis of Credit Risk Prediction for Small and Micro Enterprises. Journal of Artificial Intelligence Research, 1(2), 1-14. https://doi.org/10.70891/JAIR.2024.110004