Role of Generalised Linear Model in non-life pricing Phase3

Before reading this article, make sure that you read phase1 and phase2. Here are the link:
Phase2: 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…

Difference between Insurance and Assurance ?


  • It is a financial protection against something that might happen. Ex: Car insurance for car crash or House insurance for your house going on fire.
  • A life insurance policy, for example, provides coverage to an individual for a specified period of time. If the individual dies during that specific period, the insurance carrier will pay the amount of money agreed upon in the contract.
  •  If the insured individual lives past the specified time period, the insurance policy becomes void, and the provider is not obligated to make any payment.

so Term is Insurance.


  • It is protection against something that will happen. For ex: Life assurance because you will die.
  • A life assurance policy will always result in a payment being made because the investment is combined with the sum insured.

Note: In insurance sector , Both Insurance and Assurance are used Interchangeably. To counter this, companies now offer detailed guides to their customers containing information that satisfies customer needs and answers frequently asked questions.


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