As we all know, high-tech industry is an indispensable and important economic support for every country or region. While especially in China, the development of high-tech industry is the main driving force of economic restructuring, so how to support the rapid and better development of high-tech industry has become one of the practical problems that need to be solved. However, as the leading part of the national economy, high-tech industry is facing the problem of financing difficulty. This is mainly due to information asymmetry caused by the barrier (Zhang, 2011). According to Guiso(1998)'s research, high-tech companies are more likely to be exposed to credit markets than those engaged in traditional investment projects. And compared with traditional industries, high-tech industry has the characteristics of high risk and large investment, so the uncertainty is relatively high, which deepens the impact of information asymmetry, resulting in financing difficulties from time to time (Zhang et al., 2013). Therefore, in order to solve this problem, it is necessary to speed up the construction of high-tech enterprise credit system. This blog is mainly to discuss the relationship between high-tech enterprises and credit risk and how to establish targeted high-tech enterprises credit risk evaluation index system.
Source: Eurostat (htec_trd_group4)
According to Zhang et al. (2013)'s research, taking listed companies in China's high-tech industry as samples, Cox model was used to analyze the factors influencing the credit risk of Chinese high-tech enterprises. The results show that the company's financial status, especially liquidity ratio, receivables turnover, ROE and so on, have a significant impact on the credit risk of high-tech enterprises. In terms of independent innovation capability, the stronger the independent innovation capability, the lower the credit risk of high-tech enterprises. This shows that there is a significant negative correlation between independent innovation capability and credit. This makes us unable to help considering whether other factors, such as region, are related to the credit risk of high-tech enterprises? It also leaves the reader with something to think about.
Generally speaking, enterprise credit evaluation methods include Z score, Logistic regression model, MHDIS model, artificial neural network, fuzzy comprehensive evaluation method, fuzzy integral method and so on (Zhang, 2011). Therefore, introducing the uncertainty measure model into the credit rating of high-tech enterprises can solve the uncertainty of many factors in the credit rating system of high-tech enterprises on the one hand, and carry out quantitative analysis on it on the other hand (Zhang, 2011). And when constructing the credit risk evaluation index system of high-tech enterprises, the factors such as liquidity ratio, receivables turnover rate and independent innovation ability should be considered comprehensively to scientifically evaluate the credit status of high-tech enterprises (Zhang et al., 2013). On the other hand, when commercial banks and other financial institutions make loan decisions for high-tech enterprises, they should distinguish high-tech industries from traditional industries and take independent innovation ability into consideration, so as to facilitate the financing of high-tech enterprises (Zhang et al., 2013).
Establishing an effective evaluation index system for the credit risk of high-tech enterprises is conducive to scientific evaluation of the credit status of high-tech enterprises, reducing the possibility of information asymmetry, and thus reducing the credit risk (Zhang, 2011). From the macro point of view, but also conducive to promote financial resources flow to the technology industry, economic structure adjustment. It is very important to suggest effective risk rating methods not only for the credit risk evaluation index system of high-tech enterprises, but also for any enterprise. Now credit risk has become one of the core subjects of risk management (Aguais, 2001). Only by recognizing the complexity of credit risk can we better measure the risk, and thus manage and optimize the risk and return. This blog is about high-tech companies and credit risk. The credit risk of SMEs will continue in the next blog post.
Author: Yue PAN
Date: 11.10.2021
Reference:
Aguais, S.D. and Rosen, D., 2001. Enterprise Credit Risk Management.
Guiso, L., 1998. High-tech firms and credit rationing. Journal of Economic Behavior & Organization, 35(1), pp.39-59.
Zhang, M., 2011, May. Application of unascertained measure model in credit evaluation of high-tech enterprise. In 2011 International Conference on Business Management and Electronic Information (Vol. 4, pp. 321-325). IEEE.
Zhang, M., He, Y. and Zhou, Z.F., 2013. Study on the influence factors of high-tech enterprise credit risk: Empirical evidence from China's listed companies. Procedia Computer Science, 17, pp.901-910.
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