PE-EDD:An efficient peer-effect-based financial fraud detection approach in publicly traded China firms

作     者：Hui Xia Hui Ma Ping Cheng 

作者机构：School of accountingChongqing University of TechnologyChongqingChina Chongqing Rural Commercial BankChongqingChina 

出 版 物：《CAAI Transactions on Intelligence Technology》 (智能技术学报（英文）)

年 卷 期：2022年第7卷第3期

页      面：469-480页

核心收录：

学科分类：0810[工学-信息与通信工程] 1205[管理学-图书情报与档案管理] 07[理学] 0839[工学-网络空间安全] 0835[工学-软件工程] 0701[理学-数学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the Science and Technology Research Project of Chongqing Education Commission(KJQN201801103) the Humanities and Social Science Research Project of Chongqing Education Commission(20SKGH176) the General Funded Projects of Chinese Postdoctoral Science Foundation(2021M693764). 

主　　题：detection financial fraud NMF peer effect 

摘      要：Financial fraud arises from the exaggeration of business interests,and an accurate detection or prediction is a useful tool for both corporate management and capital market systems.A collection of computer technologies has been made on this problem so far,and one of the most important solutions is unsupervised learning algorithms.Among them,most approaches work by analysing the internal relations in financial data and finding a new description of non-fraud firms.However,current studies focus a lot on the geometry attribute of financial data,while overlooking the obvious behaviour patterns and peer effects among firms.This has limited the accuracy of representation and furthermore the detection performance.In this work,a very general class of functions is allowed to represent firms,constraining them by peer effects between firms and presenting an error-distribution-based financial fraud firm detection approach.Experimental results have shown great performance of the proposed approach.