Findings from Reykjavik University Reveals New Findings on Insurance (Social Network Analytics for Supervised Fraud Detection In Insurance): Insurance

2022 SEP 13 (NewsRx) -- By a News Reporter-Staff News Editor at NewsRx Policy and Law Daily -- Investigators publish new report on Insurance. According to news reporting out of Reykjavik, Iceland, by NewsRx editors, research stated, “Insurance fraud occurs when policyholders file claims that are exaggerated or based on intentional damages. This contribution develops a fraud detection strategy by extracting insightful information from the social network of a claim.”

Financial supporters for this research include Ageas Research chair at KULeuven, KU Leuven’s research council, EC H2020 MSCA RISE project, NeEDS research project.

Our news journalists obtained a quote from the research from Reykjavik University, “First, we construct a network by linking claims with all their involved parties, including the policyholders, brokers, experts, and garages. Next, we establish fraud as a social phenomenon in the network and use the BiRank algorithm with a fraud-specific query vector to compute a fraud score for each claim. From the network, we extract features related to the fraud scores as well as the claims’ neighborhood structure. Finally, we combine these network features with the claim-specific features and build a supervised model with fraud in motor insurance as the target variable. Although we build a model for only motor insurance, the network includes claims from all available lines of business. Our results show that models with features derived from the network perform well when detecting fraud and even outperform the models using only the classical claim-specific features. Combining network and claim-specific features further improves the performance of supervised learning models to detect fraud. The resulting model flags highly suspicions claims that need to be further investigated.”

According to the news editors, the research concluded: “Our approach provides a guided and intelligent selection of claims and contributes to a more effective fraud investigation process.”

This research has been peer-reviewed.

For more information on this research see: Social Network Analytics for Supervised Fraud Detection In Insurance. Risk Analysis, 2022;42(8):1872-1890. Risk Analysis can be contacted at: Wiley, 111 River St, Hoboken 07030-5774, NJ, USA. (Wiley-Blackwell - http://www.wiley.com/; Risk Analysis - http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1539-6924)

Our news journalists report that additional information may be obtained by contacting Maria Oskarsdottir, Reykjavik University, Dept. of Computer Sciences, Menntavegur 1, Is-102 Reykjavik, Iceland. Additional authors for this research include Waqas Ahmed, Remi Dendievel, Tom Donas, Katrien Antonio, Bart Baesens and Tom Reynkens.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1111/risa.13693. 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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