An optimal weighted machine learning model for detecting financial fraud

Minghuan Shou, Xueqi Bao, Jie Yu

Research output: Journal PublicationArticlepeer-review


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.

Original languageEnglish
JournalApplied Economics Letters
Publication statusAccepted/In press - 2021
Externally publishedYes


  • Financial fraud
  • feature selection
  • machine learning
  • weighted model

ASJC Scopus subject areas

  • Economics and Econometrics


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