{"title":"基于时间知识图的中小企业信用风险评估","authors":"Chuanyang Hong, Mengyuan Tan, Siyu Wang, Junliang Wang, Mu Li, Jiangtao Qiu","doi":"10.1109/ICCICC53683.2021.9811323","DOIUrl":null,"url":null,"abstract":"Credit Risk Assessment (CRA) is a challenging task in the financial field. Previous studies mainly focus on large firms with more comprehensive data especially financial data, annual reports, but for Small and Medium-sized Enterprises (SMEs), there is only public data to utilize, such as news, cases, etc. To better assess risk for SMEs, we constructed a temporal knowledge graph by using public data and proposed a credit risk assessment model (short for TKG-CRA) which comprehensively considers the topological structure of the temporal enterprise knowledge graph with the spread of risks and the neighbor node sequence. Experiments on real-world datasets prove that our model has a larger performance improvement than other traditional methods.","PeriodicalId":101653,"journal":{"name":"2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Small and Medium-sized Enterprises Credit Risk Assessment Based on Temporal Knowledge Graphs\",\"authors\":\"Chuanyang Hong, Mengyuan Tan, Siyu Wang, Junliang Wang, Mu Li, Jiangtao Qiu\",\"doi\":\"10.1109/ICCICC53683.2021.9811323\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Credit Risk Assessment (CRA) is a challenging task in the financial field. Previous studies mainly focus on large firms with more comprehensive data especially financial data, annual reports, but for Small and Medium-sized Enterprises (SMEs), there is only public data to utilize, such as news, cases, etc. To better assess risk for SMEs, we constructed a temporal knowledge graph by using public data and proposed a credit risk assessment model (short for TKG-CRA) which comprehensively considers the topological structure of the temporal enterprise knowledge graph with the spread of risks and the neighbor node sequence. Experiments on real-world datasets prove that our model has a larger performance improvement than other traditional methods.\",\"PeriodicalId\":101653,\"journal\":{\"name\":\"2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCICC53683.2021.9811323\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCICC53683.2021.9811323","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Small and Medium-sized Enterprises Credit Risk Assessment Based on Temporal Knowledge Graphs
Credit Risk Assessment (CRA) is a challenging task in the financial field. Previous studies mainly focus on large firms with more comprehensive data especially financial data, annual reports, but for Small and Medium-sized Enterprises (SMEs), there is only public data to utilize, such as news, cases, etc. To better assess risk for SMEs, we constructed a temporal knowledge graph by using public data and proposed a credit risk assessment model (short for TKG-CRA) which comprehensively considers the topological structure of the temporal enterprise knowledge graph with the spread of risks and the neighbor node sequence. Experiments on real-world datasets prove that our model has a larger performance improvement than other traditional methods.