Felixkkiprono/Mobile-Money-and-Financial-Inclusion-in-Tanzania-Challenge

Only 16.7% of the population in Tanzania has a bank account. But an additional 48.6% of Tanzanians who don’t have a bank account do have other types of formal financial services, primarily mobile money. For people who have been traditionally excluded from the formal financial system in Africa and other developing markets, mobile money has become an important entry point to financial inclusion. While mobile money is a tool for transferring money among people and businesses/other institutions, it is increasingly becoming a platform for people to access a broad range of financial services, including savings, credit, and insurance. The objective of this competition is to create a machine learning model to predict which individuals are most likely to use mobile money and other financial services (savings, credit, and insurance). This model can help mobile money providers target new clients and markets across Tanzania more effectively, and also help financial services providers cross-sell other financial services (savings, credit, and insurance) to the existing mobile money customer base. # Mobile-Money-and-Financial-Inclusion-in-Tanzania-Challenge Only 16.7% of the population in Tanzania has a bank account. But an additional 48.6% of Tanzanians who don’t have a bank account do have other types of formal financial services, primarily mobile money. For people who have been traditionally excluded from the formal financial system in Africa and other developing markets, mobile money has become an important entry point to financial inclusion. While mobile money is a tool for transferring money among people and businesses/other institutions, it is increasingly becoming a platform for people to access a broad range of financial services, including savings, credit, and insurance. The objective of this competition is to create a machine learning model to predict which individuals are most likely to use mobile money and other financial services (savings, credit, and insurance). This model can help mobile money providers target new clients and markets across Tanzania more effectively, and also help financial services providers cross-sell other financial services (savings, credit, and insurance) to the existing mobile money customer base. Here is the link to the competition(zindi.africa) i built three models gradient boosting algorithms:-GBM,XGboost and Catboost.