This survey paper categorises, compares, and summarises from almost all published technical and review articles in automated fraud detection within the last 10 years. It defines the professional fraudster, formalises the main types and subtypes of known fraud, and presents the nature of data evidence collected within affected industries. Within the business context of mining the data to achieve higher cost savings, this research presents methods and techniques together with their problems. Compared to all related reviews on fraud detection, this survey covers much more technical articles and is the only one, to the best of our knowledge, which proposes alternative data and solutions from related domains.
Also focused on detecting financial fraud, Reference REF conducted a survey that categorized, compared and summarized several published technical and review articles on automated fraud detection by applying data mining techniques.
A Comprehensive Survey of Data Mining-based Fraud Detection Research
ArXiv
ArXiv
Computer Science