An optimal weighted machine learning model for detecting financial fraud

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.

KEYWORDS:

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

JEL CLASSIFICATION:

• C53
• E44

Disclosure statement

No potential conflict of interest was reported by the author(s).