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- W3159796831 abstract "Forecasts of premium income are of significant importance to insurance companies. There is much room for improvement in the accuracy of these predictions. Therefore, the objective of this paper is to find the optimal model for providing forecasts of premiums. The forecast performance and interpretability of different prediction methods are analyzed. In addition, fundamental principles of survival analysis are discussed. The first model that is examined is a Cox proportional hazards model including shared frailty. It is estimated using a penalized likelihood estimation. The second model under examination is a regressive logistic regression model and is estimated by using maximum likelihood estimation. While both models are considered equally apprehensible, the latter is found to have a significantly better forecast performance. Lastly, confidence intervals for the total expected premium income are calculated." @default.
- W3159796831 created "2021-05-10" @default.
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- W3159796831 date "2021-01-01" @default.
- W3159796831 modified "2023-09-24" @default.
- W3159796831 title "Forecasting Lapse, Renewal, and Commencement of Policies in Non-Life Insurance" @default.
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