Detecting financial misstatements with fraud intention using multi-class cost-sensitive learning

作者：

Highlights：

• Multi-class financial misstatement detection models are developed.

• The models classify financial misstatements according to fraud intention.

• MetaCost is employed to perform cost-sensitive learning in a multi-class setting.

• Features are evaluated to detect fraud intention and material misstatements.

摘要

•Multi-class financial misstatement detection models are developed.•The models classify financial misstatements according to fraud intention.•MetaCost is employed to perform cost-sensitive learning in a multi-class setting.•Features are evaluated to detect fraud intention and material misstatements.

论文关键词：Financial misstatement detection,Financial restatements,Fraud intention,Multi-class cost sensitive learning

论文评审过程：Received 3 February 2016, Revised 12 April 2016, Accepted 9 June 2016, Available online 11 June 2016, Version of Record 16 June 2016.

论文官网地址：https://doi.org/10.1016/j.eswa.2016.06.016