An optimal weighted machine learning model for detecting financial fraud

Minghuan Shou, Xueqi Bao, Jie Yu

Research output: Journal PublicationArticlepeer-review

2 Citations (Scopus)


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
Pages (from-to)410-415
Number of pages6
JournalApplied Economics Letters
Issue number4
Early online date6 Oct 2021
Publication statusPublished - 2023


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

ASJC Scopus subject areas

  • Economics and Econometrics


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