Financial Fraud: A Review of Anomaly Detection Techniques and Recent Advances

作者：

Highlights：

• This survey includes the most popular and effective anomaly detection techniques.

• Highlights recent advancements in semi-supervised and unsupervised learning.

• Comprehensive discussion in financial fraud applications.

• This survey will form a foundation for future research in the area.

摘要

•This survey includes the most popular and effective anomaly detection techniques.•Highlights recent advancements in semi-supervised and unsupervised learning.•Comprehensive discussion in financial fraud applications.•This survey will form a foundation for future research in the area.

论文关键词：Index Terms — Anomaly,Outlier,Anomaly detection,Outlier detection,Machine learning,Deep learning,Financial fraud,Credit card fraud,Insurance fraud,Securities and commodities fraud,Insider trading,Money laundering

论文评审过程：Received 11 July 2021, Revised 17 December 2021, Accepted 18 December 2021, Available online 31 December 2021, Version of Record 20 January 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.116429