Concordance probability in a big data setting: application in non-life\n insurance

2019/11/14 by Robin Van Oirbeek, Van Oirbeek, Robin, Christopher Grumiau +3
Computer Science · Decision Sciences · Mathematics · #Advanced Statistical Methods and Models #Advanced Statistical Process Monitoring #Analysis of PDEs (math.AP) #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Statistical Methods and Inference

paper · pdf · doi:10.48550/arxiv.1911.06187

openalex publication_date 2019/11/14 · openalex created_date 2022/10/05 · openalex updated_date 2026/07/28

Abstract

The concordance probability or C-index is a popular measure to capture the\ndiscriminatory ability of a regression model. In this article, the definition\nof this measure is adapted to the specific needs of the frequency and severity\nmodel, typically used during the technical pricing of a non-life insurance\nproduct. Due to the typical large sample size of the frequency data in\nparticular, two different adaptations of the estimation procedure of the\nconcordance probability are presented. Note that the latter procedures can be\napplied to all different versions of the concordance probability.\n

Citations

• The area above the ordinal dominance graph and the area below the receiver operating characteristic graph

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