Pricing Strategy From Concurrence Open Data
Leveraging Competitive Analysis from Open Data and ML Models for a National Insurer
Context & Objectives

The project objective consists of understanding a competitive pricing analysis of a national insurer on several relevant segments in order to optimize pricing and reduce adverse selection risks.


The tool has become the reference to analyze competitive pricing and optimize pricing strategy accordingly.

Our approach

Step 1 - Audit

  • Generate numerous customer profiles and gather competitive data via web scrapping (GANs methods)

Step 2 - Reverse-Engineer

  • Reverse-engineer the pricing strategy of the competitors : from competitive pricing data and using interpretability technics of « black box » Machine Learning models, the tariff positioning is then understandable and integrated into the tool (use of the x-shap method)

Step 3 - Build

  • Build a visualization tool for business analysts
Our experts
Aimé Lachapelle
Managing Partner
Julie Caredda
Related Capabilities
Related Industries