JOINT MODEL PREDICTION AND APPLICATION TO INDIVIDUAL-LEVEL LOSS RESERVING

DOI10.1017/asb.2021.28zbMath1484.91401OpenAlexW3212129041MaRDI QIDQ5067883

A. Nii-Armah Okine, Peng Shi, Edward W. Frees

Publication date: 4 April 2022

Published in: ASTIN Bulletin (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1017/asb.2021.28

zbMATH Keywords

dynamic predictionRBNS reservesjoint model for longitudinal and survival datamicro-level loss reserving

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Actuarial mathematics (91G05)

Related Items

MULTI-STATE MODELLING OF CUSTOMER CHURN ⋮ Collective reserving using individual claims data ⋮ Transaction time models in multi-state life insurance

Uses Software

• ChainLadder
• JM
• JMbayes

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• A marked Cox model for the number of IBNR claims: theory
• Neural networks applied to chain-ladder reserving
• A micro-level claim count model with overdispersion and reporting delays
• Joint Models for Longitudinal and Time-to-Event Data
• Fully Exponential Laplace Approximations for the Joint Modelling of Survival and Longitudinal Data
• A Semiparametric Likelihood Approach to Joint Modeling of Longitudinal and Time-to-Event Data
• Joint modelling of longitudinal and time-to-event data with application to predicting abdominal aortic aneurysm growth and rupture
• Summarizing Insurance Scores Using a Gini Index
• Shared parameter models under random effects misspecification
• Prediction of Outstanding Liabilities II. Model Variations and Extensions
• A Joint Model for Survival and Longitudinal Data Measured with Error
• Micro-level stochastic loss reserving for general insurance
• Machine learning in individual claims reserving
• Longitudinal and Panel Data
• Informative Drop-Out in Longitudinal Data Analysis
• A MARKED COX MODEL FOR THE NUMBER OF IBNR CLAIMS: ESTIMATION AND APPLICATION
• A TREE-BASED ALGORITHM ADAPTED TO MICROLEVEL RESERVING AND LONG DEVELOPMENT CLAIMS
• Joint modelling of longitudinal measurements and event time data