Marketing Intelligence Assignment

Client Needs & Objectives


  • Massive clients databases are not fully exploited
  • The use of a machine learning modelling enables to offer additional options and products depending on clients’ characteristics
  • A good modelling of customers’ specifications allows for efficient targeting and high probability of complementary options underwriting


Exploitation of customers databases in order to refine the insurance offer of products and complementary options according to clients’ profiles


  • Insurance policies proposals
  • Fraud detection
  • Credit risk


  • Logistic regression
  • Neural network
  • Random forest

Our approach

  • Segmentation of the database in 2 sub-bases: the first sub-base as a learning tool and the second one for model testing
  • Initialization of coefficients and calibration of parameters via machine learning modelling in the learning base to optimize the predictive power on the test base
  • Extension of the model to the entire base
  • Exploitation of the data with different machine learning models
  • Selection of the best model through cross-validation
  • Focus on the three products or additional options  the most likely to be underwritten

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