Research Conducted at McGill University Has Provided New Information about Bayesian Analysis (A Bayesian Approach To Modeling Multivariate Multilevel Insurance Claims In the Presence of Unsettled Claims): Bayesian Analysis

2022 MAR 24 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Researchers detail new data in Bayesian Analysis. According to news originating from Montreal, Canada, by NewsRx correspondents, research stated, “A Bayesian model for individual insurance claims is proposed which accounts for the multivariate multilevel features of the claims, including multiple claimants for the same event, each of whom may receive benefits under different coverages. A Bayesian approach makes it possible to account for missing values in the covariates and partial information contained in open files, thereby avoiding sampling bias induced when unsettled claims are ignored.”

Financial supporters for this research include Natural Sciences and Engineering Research Council of Canada (NSERC), Society of Actuaries James C. Hickman Scholar program, Canada Research Chairs, James McGill Research Chairs program, NSERC’s Discovery Grant program.

Our news journalists obtained a quote from the research from McGill University, “For a given claim, the combination of coverages under which payments are made is modeled as a type with multinomial regression. The presence of legal and expert fees follows a logistic regression given the type. The non-zero claim amounts are then modeled with log skewed normal regressions linked by a Student t copula. The Bayesian framework yields a predictive distribution for the amounts paid, including parameter risk and process risk, while handling missing covariates and open files.”

According to the news editors, the research concluded: “The approach is illustrated with Accident Benefits car insurance claims from a Canadian company.”

This research has been peer-reviewed.

For more information on this research see: A Bayesian Approach To Modeling Multivariate Multilevel Insurance Claims In the Presence of Unsettled Claims. Bayesian Analysis, 2022;17(1):67-93. Bayesian Analysis can be contacted at: Int Soc Bayesian Analysis, Carnegie Mellon Univ, Dept Sttistics, Pittsburgh, PA 15213, USA.

The news correspondents report that additional information may be obtained from Christian Genest, McGill University, Dept. of Mathematics and Statistics, 805 Rue Sherbrooke Ouest, Montreal, Pq H3A 0B9, Canada. Additional authors for this research include Marie-Pier Cote and David A. Stephens.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1214/20-BA1243. 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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