Multiclass Cross-selling Model for Savings and Investments Using Gradient Boosting

Abstract: Danske Bank has for several years modeled customer purchase behavior on category level (e.g. savings or investments). This thesis is a first attempt at predicting (first time) customer purchase behavior on product level. Five products within two categories were chosen and modelling was done with python using gradient boosters (mainly XGBoost, but also Light GBM). Results indicated that predicting product purchase is possible, although not with the target selected for this thesis. Multiclass modelling gives additional insight into customer behavior compared to models on category level, however, additional tuning of the models are required before the accuracy reaches the same level as the category prediction models.