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

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/