Pricing strategy with competitor open data

Context and objectives

The objective was to analyse the competitive pricing of a national insurer on several relevant segments, in order to optimise its pricing and reduce adverse selection risk.

Outcome

The tool has become the reference for analysing competitive pricing and optimising the pricing strategy accordingly.

Our approach

Step 1: data collection

• Generation of many customer profiles and collection of competitive data through web scraping (GAN methods)

Step 2: reverse engineering

• Reverse engineering of competitors' pricing strategies: using competitive pricing data and interpretability techniques for black-box machine learning models (the X-SHAP method), tariff positioning becomes understandable and is integrated into the tool

Step 3: build

• A visualisation tool for business analysts