{"title":"天池金融风险中的客户违约风险评价","authors":"None Chuhan Su","doi":"10.61173/ry2b9753","DOIUrl":null,"url":null,"abstract":"Based on the PCA(principal component analysis) and logistic regression model, this essay evaluates the default Risk of the borrowers’ information in the Tianchi Financial Risk dataset. The research finds that the default rate is the main factor affecting Tianchi Financial Risk. Combining borrowers’ credit grades with factors influencing the default rate, the logistic regression analysis is conducted. It is concluded that individuals with a step above D have a high risk of default, whereas those with a grade below D have low-risk defaults.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2023-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluation of Customer Default Risk in Tianchi Financial risk\",\"authors\":\"None Chuhan Su\",\"doi\":\"10.61173/ry2b9753\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on the PCA(principal component analysis) and logistic regression model, this essay evaluates the default Risk of the borrowers’ information in the Tianchi Financial Risk dataset. The research finds that the default rate is the main factor affecting Tianchi Financial Risk. Combining borrowers’ credit grades with factors influencing the default rate, the logistic regression analysis is conducted. It is concluded that individuals with a step above D have a high risk of default, whereas those with a grade below D have low-risk defaults.\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2023-10-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.61173/ry2b9753\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.61173/ry2b9753","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
Evaluation of Customer Default Risk in Tianchi Financial risk
Based on the PCA(principal component analysis) and logistic regression model, this essay evaluates the default Risk of the borrowers’ information in the Tianchi Financial Risk dataset. The research finds that the default rate is the main factor affecting Tianchi Financial Risk. Combining borrowers’ credit grades with factors influencing the default rate, the logistic regression analysis is conducted. It is concluded that individuals with a step above D have a high risk of default, whereas those with a grade below D have low-risk defaults.
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