TY - JOUR
T1 - An optimal weighted machine learning model for detecting financial fraud
AU - Shou, Minghuan
AU - Bao, Xueqi
AU - Yu, Jie
N1 - Publisher Copyright:
© 2021 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2021
Y1 - 2021
N2 - The purpose of this study is to predict enterprises’ financial fraud. After collecting financial data and employing feature selection methods, totally eight features are selected. We select two best-performance machine learning models according to five indicators including accuracy, recall, specificity, AUC and the misclassification cost. Besides, an optimal weighted machine learning model, based on the two best-performance models, is proposed and the results confirm its good performance in forecasting enterprises’ financial fraud.
AB - The purpose of this study is to predict enterprises’ financial fraud. After collecting financial data and employing feature selection methods, totally eight features are selected. We select two best-performance machine learning models according to five indicators including accuracy, recall, specificity, AUC and the misclassification cost. Besides, an optimal weighted machine learning model, based on the two best-performance models, is proposed and the results confirm its good performance in forecasting enterprises’ financial fraud.
KW - Financial fraud
KW - feature selection
KW - machine learning
KW - weighted model
UR - http://www.scopus.com/inward/record.url?scp=85116493944&partnerID=8YFLogxK
U2 - 10.1080/13504851.2021.1989367
DO - 10.1080/13504851.2021.1989367
M3 - Article
AN - SCOPUS:85116493944
JO - Applied Economics Letters
JF - Applied Economics Letters
SN - 1350-4851
ER -