Role of Generalised Linear Model in non-life pricing Phase3

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Before reading this article, make sure that you read phase1 and phase2. Here are the link:
Phase1: http://www.actuarysense.com/2018/10/role-of-generalised-linear-model-in-non.html
Phase2: http://www.actuarysense.com/2018/11/role-of-generalised-linear-model-in-non.html So we know that the purpose of GLM is to find the relationship between mean of the response variable and covariates.

In this Article we are going to talk about Linear Predictors.
Linear Predictor: Let’s denote it with, “η” (eta). So, linear predictor is actually a function of covariates. For example, in the normal linear model where function is Y = B0 + B1x. So linear predictor will be η = B0 + B1x. Always note that linear predictor has to be linear in its parameter. In this case parameters are B0 and B1. But still the question is how I came up with B0 + B1x as a function? First of all, note that broadly there are two types of Covariates. 1. Variables: It takes the numerical value. For example: age of policyholder, years of ex…

What is the difference between Select Mortality and Ultimate Mortality?

ULTIMATE MORTALITY:

A simple life mortality table classifies people by attained age and assumes each attained age (or possibly age range) is subject to some rate of mortality. Another way of saying this is the mortality depends on only one variable, attained age.





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SELECT MORTALITY:
Since most life insurance involves some kind of underwriting or selection process, it may be interesting to look at the mortality based on two variables, age at selection and duration since selection. This produces a two-dimensional table; that table is Select mortality table.


NOTE:
  • ·        A select mortality table includes mortality data on individuals who have recently purchased life insurance. These individuals tend to have lower mortality rates than individuals who are already insured, due chiefly to the fact that they have most likely just passed certain medical exams required to obtain insurance.
  • ·        some period of years after the selection (say 10 years) the only factor that affects the mortality rate is the attained age. For example, if underwriting wears off after 10 years, the mortality rate is the same for persons who are now age 60, as long as they were selected before age 50.

  • The length of time that the rate depends on two variables is called the select period.



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