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Old 06-13-2018, 04:18 PM
Marco_park Marco_park is offline
Join Date: Jan 2018
Posts: 4
Default Ratemaking Model

Hi All,

we are trying to assess the financial impact deriving from an improvement in a ratemaking model.

In particular we are moving from a standard GLM approach towards a more sophisticated one using Machine Learning.

We have also estimated the increase of the Gini index of both, the current and the proposed pricing approach.

Our doubts are related to how to quantify the financial impact in terms of possible monetary gain due to the model change.

We are aware that our proposed model is more precise, but how to quantify the possible financial impact from a monetary point of view?

Is there any theoretical and practical framework to address this?
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Old 06-14-2018, 08:53 AM
sticks1839 sticks1839 is offline
Join Date: Jul 2005
Posts: 1,562

Think about what will happen if/when you implement the new model. Some customers will see prices go up and some will see prices go down. Assuming they are price elastic, you should see a mix shift in your book. If the new model is truly better, then that mix shift will be favorable because it will lessen the opportunity for adverse selection.

You can calculate this impact by making assumptions about that elasticity and the future state of your book. Overall, whether via mix or price corrections, you should see an improved loss ratio.
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machine learning, pricing, ratemaking

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