New Machine Learning Findings from University of Orleans Described (Practical Guideline To Efficiently Detect Insurance Fraud In the Era of Machine Learning: a Household Insurance Case): Machine Learning

2023 DEC 29 (NewsRx) -- By a News Reporter-Staff News Editor at NewsRx Policy and Law Daily -- Current study results on Machine Learning have been published. According to news originating from Orleans, France, by NewsRx correspondents, research stated, “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.”

Funders for this research include Data Science and Insurance Fraud Detection research initiative under the aegis of the Europlace Institut of Finance, Laboratoired ‘Economie d’Orleans and Thelem Assurances, Fraud Detection and Anti-Money Laundering research project - Centre-Val de Loire Region.

Our news journalists obtained a quote from the research from the University of Orleans, “Several methods are developed to identify risk factors and unusual customer behaviors. Traditional econometric models as well as new machine-learning algorithms with good predictive performance and high operational efficiency are tested, while maintaining method interpretability. Each methodology is evaluated on the basis of adequate performance measures and the issue of imbalanced databases is also addressed.”

According to the news editors, the research concluded: “Finally, specific methods are applied to interpret the results of the machine-learning methods.”

This research has been peer-reviewed.

For more information on this research see: Practical Guideline To Efficiently Detect Insurance Fraud In the Era of Machine Learning: a Household Insurance Case. Journal of Risk & Insurance, 2023. Journal of Risk & Insurance can be contacted at: Wiley, 111 River St, Hoboken 07030-5774, NJ, USA. (Wiley-Blackwell - http://www.wiley.com/; Journal of Risk & Insurance - http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1539-6975)

The news correspondents report that additional information may be obtained from Denisa Banulescu-Radu, University of Orleans, Leo, Orleans, France.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1111/jori.12452. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

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