Practical guideline to efficiently detect insurance fraud in the era of machine learning: A household insurance case
Denisa Banulescu‐Radu,
Meryem Yankol‐Schalck
Abstract:Identifying insurance fraud is a difficult task due to the complex nature of the fraud itself, the diversity of techniques employed, the rarity of fraud cases observed in data sets, and the relatively limited allocation of human, financial, and time resources to carry out investigations. The aim of this paper is to provide a clean and well structured study on modeling fraud on home insurance contracts, using real French data from 2013 to 2017. Several methods are developed to identify risk factors and unusual … Show more
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