{"title":"系统风险与银行网络：知识图谱与 ChatGPT 的应用","authors":"Ren-Yuan Lyu, Ren-Raw Chen, San-Lin Chung, Yilu Zhou","doi":"10.3390/fintech3020016","DOIUrl":null,"url":null,"abstract":"In this paper, we study the networks of financial institutions using textual data (i.e., news). We draw knowledge graphs after the textual data has been processed via various natural language processing and embedding methods, including use of the most recent version of ChatGPT (via OpenAI api). Our final graphs represent bank networks and further shed light on the systemic risk of the financial institutions. Financial news reflects live how financial institutions are connected, via graphs which provide information on conditional dependencies among the financial institutions. Our results show that in the year 2016, the chosen 22 top U.S. financial firms are not closely connected and, hence, present no systemic risk.","PeriodicalId":472258,"journal":{"name":"FinTech","volume":"29 5","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Systemic Risk and Bank Networks: A Use of Knowledge Graph with ChatGPT\",\"authors\":\"Ren-Yuan Lyu, Ren-Raw Chen, San-Lin Chung, Yilu Zhou\",\"doi\":\"10.3390/fintech3020016\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we study the networks of financial institutions using textual data (i.e., news). We draw knowledge graphs after the textual data has been processed via various natural language processing and embedding methods, including use of the most recent version of ChatGPT (via OpenAI api). Our final graphs represent bank networks and further shed light on the systemic risk of the financial institutions. Financial news reflects live how financial institutions are connected, via graphs which provide information on conditional dependencies among the financial institutions. Our results show that in the year 2016, the chosen 22 top U.S. financial firms are not closely connected and, hence, present no systemic risk.\",\"PeriodicalId\":472258,\"journal\":{\"name\":\"FinTech\",\"volume\":\"29 5\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"FinTech\",\"FirstCategoryId\":\"0\",\"ListUrlMain\":\"https://doi.org/10.3390/fintech3020016\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"FinTech","FirstCategoryId":"0","ListUrlMain":"https://doi.org/10.3390/fintech3020016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Systemic Risk and Bank Networks: A Use of Knowledge Graph with ChatGPT
In this paper, we study the networks of financial institutions using textual data (i.e., news). We draw knowledge graphs after the textual data has been processed via various natural language processing and embedding methods, including use of the most recent version of ChatGPT (via OpenAI api). Our final graphs represent bank networks and further shed light on the systemic risk of the financial institutions. Financial news reflects live how financial institutions are connected, via graphs which provide information on conditional dependencies among the financial institutions. Our results show that in the year 2016, the chosen 22 top U.S. financial firms are not closely connected and, hence, present no systemic risk.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
