An optimal weighted machine learning model for detecting financial fraud

Minghuan Shou, Xueqi Bao, Jie Yu

Research output: Journal PublicationArticlepeer-review

Abstract

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
DOIs
Publication statusAccepted/In press - 2021
Externally publishedYes

Keywords

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

ASJC Scopus subject areas

  • Economics and Econometrics

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