Predictive Modeling to Investigate and Forecast Customer Behaviour in the Banking Sector

Analyzing the tremendous amount of data that the banking industry generates has become a critical step for financial institutions. Firms that fail to leverage the huge stream of data they are able to collect, risk falling behind and missing out on the full benefits that this in-depth and extensive analysis can bring. From better understanding customer behavior and needs to making accurate and profitable decisions, data mining has proven its usefulness and enormous benefits and is now widely recognized as a key component for banks. This study aims to highlight the importance and usefulness of implementing data science algorithms and methods to study customer behavior in the banking sector. The research is based on a case study of a bank in Tunisia where the main focus behind is to assess the risk and creditworthiness of a loan applicant and to eventually determine whether or not these customers are worth keeping.