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Credit Risk Forecast and Assessment of Automobile Supply Chain Finance Based on Proportional Hazards Model

Published: 02 December 2021 Publication History

Abstract

Supply chain finance is developed to settle such problems, such as financing difficulties among small and medium-sized enterprises (SMEs), banks' business dilemma, and supply chain fragility. In recent year, supply chain finance in the automobile industry is developing rapidly. However, due to the complexity of automobile supply chain, there are still some business risks, among which credit risks account for a large proportion. To promote the development of automobile SMEs and reduce the risks in the financing process, we predict the potential credit risk points of the automobile industry and construct the evaluation index system. The proportional hazards model (Cox model) is estimated on data from China Stock Market & Accounting Research Database (CSMAR database). The data comprise 95 listed automobile SMEs from 2010 to 2019. The results show that two indexes (current asset turnover and shareholder equity turnover) are included in Cox model. In addition, in order to test the accuracy of Cox model, 25 enterprises compose test set. The accuracy of test results is 72%, which means that the cox model predicts well.

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Dai Xin qi. Research on Credit Risk Assessment Model of Commercial Banks – An Empirical Study Based on Online Supply Chain Finance [J]. Soft science, 2018, 32 (5): 139-144. (In Chinese)
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Fan Fangzhi, Su Guoqiang, Wang Xiaoyan. Research on credit risk evaluation and risk management of small and medium-sized enterprises in supply chain finance model [J]. Journal of Central University of Finance and Economics, 017(12):34-43. (In Chinese)
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Cited By

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  • (2024)Application and optimization of deep learning in the credit score of auto financeApplied Mathematics and Nonlinear Sciences10.2478/amns-2024-24859:1Online publication date: 3-Sep-2024
  • (2022)Cognitive bias toward the Internet: The causes of adolescents’ Internet addiction under parents’ self-affirmation consciousnessFrontiers in Psychology10.3389/fpsyg.2022.89147313Online publication date: 1-Aug-2022

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ICEME '21: Proceedings of the 2021 12th International Conference on E-business, Management and Economics
July 2021
882 pages
ISBN:9781450390064
DOI:10.1145/3481127
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 December 2021

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Author Tags

  1. Automobile industry
  2. Credit risk prediction
  3. Proportional hazards model
  4. Supply chain finance

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Cited By

View all
  • (2024)Application and optimization of deep learning in the credit score of auto financeApplied Mathematics and Nonlinear Sciences10.2478/amns-2024-24859:1Online publication date: 3-Sep-2024
  • (2022)Cognitive bias toward the Internet: The causes of adolescents’ Internet addiction under parents’ self-affirmation consciousnessFrontiers in Psychology10.3389/fpsyg.2022.89147313Online publication date: 1-Aug-2022

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