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Webinar #3 Market pricing benchmarking - How machine learning can improve reverse engineering

About this event


Agenda:

  1. Data collection for market pricing benchmarking
  2. Selecting the best machine learning models for reverse engineering
  3. Tuning the parameters and interpreting the results
  4. Prediction intervals for individual predictions
  5. Case study in R/Shiny

Abstract:

Due to the rise in the use of internet, policyholders are now able to compare insurers’ rates easily without even going to their insurer or broker. This level of transparency leads to a competition among insurers which is now fiercer than ever.

This webinar presents a framework based on predictive models which enables insurance companies to gain insights on the premiums offered by their competitors over different segments. Thanks to this kind of premium benchmark, an insurer is able to review its positioning and adapt to the evolutions of the market.

The content of this webinar comes from our White Paper “Market pricing benchmarking - How machine learning can improve reverse engineering” available on https://www.reacfin.com/index.php/2020/04/10/market-pricing-benchmarking/

Hosted by

  • Team member
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    Reacfin Academy

    Reacfin is a consulting firm focused on creating measurable value & results for its clients. Our mission is to develop innovative solutions to manage risks, products, capital & portfolios.

  • Team member
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    Sam Mahy Director - Head of Non-Life @ Reacfin

  • Team member
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    Michael Lecuivre Actuarial Consultant @ Reacfin

  • Team member
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    Marie Hainneville Trainee @ Reacfin

  • Team member
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    Xavier Maréchal CEO @ Reacfin

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