Credit Risk Evaluation on Technological SMEs in China

Abstract

China’s reform and opening-up policies have prioritized technological advancement, with technological SMEs driving employment and economic growth. Despite their significance, these SMEs face substantial financing and operational risks due to inadequate credit measurement tools. This study reviews the historical financing challenges of technological SMEs since the 1980s, summarizes their current credit risk status, and compares four modern credit risk models: Credit Metrics, Credit Risk+, Credit Portfolio View, and KMV. We propose a pioneering KMV Strategy for real-time risk analysis, contributing to accurate credit metrics for these SMEs. Finally, we suggest policies for managing their credit risks through prevention, control, and governance.

Publication DOI: https://doi.org/10.1080/17517575.2024.2374741
Divisions: College of Business and Social Sciences > Aston Business School > Operations & Information Management
College of Business and Social Sciences
College of Business and Social Sciences > Aston Business School
Funding Information: This work is partly supported by VC Research [VCR 0000099].
Additional Information: Copyright © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
Uncontrolled Keywords: Technological SMEs in China,KMV model,risk management,credit system,risk analysis and SMEs,KMV strategy
Publication ISSN: 1751-7583
Last Modified: 07 Oct 2024 07:59
Date Deposited: 30 Jul 2024 12:18
Full Text Link:
Related URLs: https://www.tan ... 75.2024.2374741 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2024
Published Online Date: 2024-07-22
Accepted Date: 2024-06-27
Authors: Chang, Victor (ORCID Profile 0000-0002-8012-5852)

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