{"title":"中小微企业的信贷决策问题","authors":"Cangshu Li, Yuewen Dang, Yinuo Liu, Xiaorong Liu, Junhong Kang, Yanshan Liao","doi":"10.22158/jepf.v8n2p48","DOIUrl":null,"url":null,"abstract":"Micro, small and medium enterprises (MSMEs) have become an important force in driving the country’s market economy in the 21st century. However, because of the following drawbacks: i.e. single enterprise capital chain, unstable economy, high risk, etc., banks will take many risks if they lend to MSMEs. Therefore, it is necessary to build a sound bank credit decision system to promote the development of MSMEs. The analytic hierarchy process (AHP) is employed to classify the importance level such as credit rating and enterprise strength are used as first-grade indexes, and six indicators in terms of total sales and total profits are used as the second-grade indexes. Then, the eigenvalue method is used to obtain the importance weights of each level of indicators, and the weights of each influencing factor at each level are then calculated to achieve a quantitative analysis of credit risk and rating of each enterprise’s credit risk. This paper combines the existing loan pricing and loan interest rates to give preferential interest rates and higher loan amounts to enterprises with excellent credit risk ratings, and to give certain risky interest rates and lower loan amounts to enterprises with medium credit risk ratings.Based on the model, a quantitative analysis of the credit risk of 302 non-credit record enterprises is carried out and the bank’ credit strategy is provided when the total annual credit is 100 million yuan. Finally, this paper comprehensively considers the impact of credit risk and unexpected factors (e.g., the COVID-19) on enterprises, and provides the bank’s credit adjustment strategy when the total annual credit is 100 million yuan.","PeriodicalId":73718,"journal":{"name":"Journal of economics and public finance","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Credit Decision Problems of MSMEs (Medium, Small and Micro-sized Enterprises)\",\"authors\":\"Cangshu Li, Yuewen Dang, Yinuo Liu, Xiaorong Liu, Junhong Kang, Yanshan Liao\",\"doi\":\"10.22158/jepf.v8n2p48\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Micro, small and medium enterprises (MSMEs) have become an important force in driving the country’s market economy in the 21st century. However, because of the following drawbacks: i.e. single enterprise capital chain, unstable economy, high risk, etc., banks will take many risks if they lend to MSMEs. Therefore, it is necessary to build a sound bank credit decision system to promote the development of MSMEs. The analytic hierarchy process (AHP) is employed to classify the importance level such as credit rating and enterprise strength are used as first-grade indexes, and six indicators in terms of total sales and total profits are used as the second-grade indexes. Then, the eigenvalue method is used to obtain the importance weights of each level of indicators, and the weights of each influencing factor at each level are then calculated to achieve a quantitative analysis of credit risk and rating of each enterprise’s credit risk. This paper combines the existing loan pricing and loan interest rates to give preferential interest rates and higher loan amounts to enterprises with excellent credit risk ratings, and to give certain risky interest rates and lower loan amounts to enterprises with medium credit risk ratings.Based on the model, a quantitative analysis of the credit risk of 302 non-credit record enterprises is carried out and the bank’ credit strategy is provided when the total annual credit is 100 million yuan. Finally, this paper comprehensively considers the impact of credit risk and unexpected factors (e.g., the COVID-19) on enterprises, and provides the bank’s credit adjustment strategy when the total annual credit is 100 million yuan.\",\"PeriodicalId\":73718,\"journal\":{\"name\":\"Journal of economics and public finance\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of economics and public finance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22158/jepf.v8n2p48\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of economics and public finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22158/jepf.v8n2p48","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Credit Decision Problems of MSMEs (Medium, Small and Micro-sized Enterprises)
Micro, small and medium enterprises (MSMEs) have become an important force in driving the country’s market economy in the 21st century. However, because of the following drawbacks: i.e. single enterprise capital chain, unstable economy, high risk, etc., banks will take many risks if they lend to MSMEs. Therefore, it is necessary to build a sound bank credit decision system to promote the development of MSMEs. The analytic hierarchy process (AHP) is employed to classify the importance level such as credit rating and enterprise strength are used as first-grade indexes, and six indicators in terms of total sales and total profits are used as the second-grade indexes. Then, the eigenvalue method is used to obtain the importance weights of each level of indicators, and the weights of each influencing factor at each level are then calculated to achieve a quantitative analysis of credit risk and rating of each enterprise’s credit risk. This paper combines the existing loan pricing and loan interest rates to give preferential interest rates and higher loan amounts to enterprises with excellent credit risk ratings, and to give certain risky interest rates and lower loan amounts to enterprises with medium credit risk ratings.Based on the model, a quantitative analysis of the credit risk of 302 non-credit record enterprises is carried out and the bank’ credit strategy is provided when the total annual credit is 100 million yuan. Finally, this paper comprehensively considers the impact of credit risk and unexpected factors (e.g., the COVID-19) on enterprises, and provides the bank’s credit adjustment strategy when the total annual credit is 100 million yuan.