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B1801
Title: In-sample hazard forecasting based on survival models with operational time applied to non-life reserving Authors:  Stephan Bischofberger - Cass Business School (United Kingdom) [presenting]
Abstract: A generalization of the accelerated failure time model allowing the covariate effect to be any positive function of the covariate is introduced. The covariate effect and the baseline hazard rate are estimated nonparametrically via an iterative algorithm. In an application in non-life reserving in actuarial science, the survival time models the development delay of a claim and the covariate effect is often called operational time. Time of underwriting serves as covariate. The estimated hazard rate is a nonparametric alternative to development factors in reserving and is used to forecast outstanding liabilities. Hence, we provide an extension of the chain-ladder framework without the assumption of independence between delay and underwriting.