{"title":"美国上市公司的会计欺诈检测:机器学习方法","authors":"Bin Li, Julia Yu, Jie Zhang, B. Ke","doi":"10.2139/SSRN.2670703","DOIUrl":null,"url":null,"abstract":"This paper studies how machine learning techniques can facilitate the detection of accounting fraud in publicly traded US rms. Existing studies often mimic human experts and employ the nancial or nonnancial","PeriodicalId":119756,"journal":{"name":"Asian Conference on Machine Learning","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Detecting Accounting Frauds in Publicly Traded U.S. Firms: A Machine Learning Approach\",\"authors\":\"Bin Li, Julia Yu, Jie Zhang, B. Ke\",\"doi\":\"10.2139/SSRN.2670703\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper studies how machine learning techniques can facilitate the detection of accounting fraud in publicly traded US rms. Existing studies often mimic human experts and employ the nancial or nonnancial\",\"PeriodicalId\":119756,\"journal\":{\"name\":\"Asian Conference on Machine Learning\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Asian Conference on Machine Learning\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/SSRN.2670703\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asian Conference on Machine Learning","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/SSRN.2670703","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detecting Accounting Frauds in Publicly Traded U.S. Firms: A Machine Learning Approach
This paper studies how machine learning techniques can facilitate the detection of accounting fraud in publicly traded US rms. Existing studies often mimic human experts and employ the nancial or nonnancial