论文标题
保险中的失误风险建模：贝叶斯混合方法
Lapse risk modelling in insurance: a Bayesian mixture approach
论文作者
论文摘要
本文着重于在人寿保险的背景下为保单持有人投降时间。在此设置中，经常观察到合同的头几个月的较高失误率，几个月后，此速度降低。取消时间的建模必须解释此特定行为。另一个风格化的事实是，在研究期间未取消的政策被认为是对的。为了说明谴责和异质失误率，这项工作假设了带有回归的混合物的贝叶斯生存模型。该推论是基于数据增强，即使对于超过一百万客户端的数据集，也可以进行快速计算。此外，还提出了基于EM算法的可扩展点估计。一个说明性的例子模仿了人寿保险合同的典型行为，模拟研究调查了拟议模型的特性。特别是，在保险环境中观察到的谴责可能是数据的50％，这对于其他领域（例如流行病学）的生存模型非常不寻常。在我们的模拟研究中利用了这一方面。
This paper focuses on modelling surrender time for policyholders in the context of life insurance. In this setup, a large lapse rate at the first months of a contract is often observed, with a decrease in this rate after some months. The modelling of the time to cancellation must account for this specific behaviour. Another stylised fact is that policies which are not cancelled in the study period are considered censored. To account for both censuring and heterogeneous lapse rates, this work assumes a Bayesian survival model with a mixture of regressions. The inference is based on data augmentation allowing for fast computations even for data sets of over a million clients. Moreover, scalable point estimation based on EM algorithm is also presented. An illustrative example emulates a typical behaviour for life insurance contracts and a simulated study investigates the properties of the proposed model. In particular, the observed censuring in the insurance context might be up to 50% of the data, which is very unusual for survival models in other fields such as epidemiology. This aspect is exploited in our simulated study.
