Feature engineering to detect fraud using healthcare claims data

作者：

Highlights：

• FWA in government administered programs is a major societal threat.

• Analytical framework to convert claims data to meaningful fraud indicators.

• Feature engineering can break or make a machine learning model.

• Using engineered features keeps fraud in check and save billions of tax dollars.

摘要

•FWA in government administered programs is a major societal threat.•Analytical framework to convert claims data to meaningful fraud indicators.•Feature engineering can break or make a machine learning model.•Using engineered features keeps fraud in check and save billions of tax dollars.

论文关键词：Medicaid,Fraud detection,Class imbalance,Machine learning,Statistical models

论文评审过程：Received 20 June 2021, Revised 1 August 2022, Accepted 4 August 2022, Available online 8 August 2022, Version of Record 24 August 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118433