Credit Risk Analysis of Micro and Small Enterprises Based on Big Data-Driven Logistic Regression Models of Bank Credit Records-Reference-Cited by-同舟云学术

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Credit Risk Analysis of Micro and Small Enterprises Based on Big Data-Driven Logistic Regression Models of Bank Credit Records

Published:2024-04-26 Issue: Volume: Page:1182-1186
ISSN:
Container-title:Proceedings of the 5th International Conference on Computer Information and Big Data Applications
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Author:

Chen Guoqing¹^ORCID,Busababodhin Piyapatr¹^ORCID,Chutiman Nipaporn¹^ORCID

Affiliation:

1. Department of Mathematics, Mahasarakham University, Thailand

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3671151.3671357

Reference15 articles.

1. Sun Y. Zeng X. Cui X. Zhang G. & Bie R. 2021. An active and dynamic credit reporting system for SMEs in China. Personal and Ubiquitous Computing 25 989-1000.

2. Xiao P. Salleh M. I. B. & Cheng J. 2022. Research on Factors Affecting SMEs’ Credit Risk Based on Blockchain-Driven Supply Chain Finance. Information 13(10) 455.

3. Data-driven decision-making in credit risk management: The information value of analyst reports

4. Big data analytics for default prediction using graph theory

5. Cheraghali H. & Molnár P. 2023. SME default prediction: A systematic methodology-focused review. Journal of Small Business Management 1-59.

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