Machine Learning Approaches for Retail Bank Marketing Practice

The retail business is usually one of the most essential bank divisions that directly handles personal customers. As restrictions for COVID-19 are gradually phasing out globally, market share banking also rapidly growing, which made improving current marketing practices necessary. However, banks lack an objective and reliable approach to locating target Meanwhile, they need affordable efficient ways process massive data generated in information systems predict purchase intent their client. This paper introduced two machine learning algorithms solve issues mentioned above, were developed on a dataset derived from Portuguese bank’s campaign. Firstly, this study trained Random Forest model help select features focus when predicting client subscription term deposit. Secondly, Artificial Neural Network was implemented evaluate probability individual customer product. proposed successfully indicates age communication with critical factors drive deposits. achieves excellent accuracy 91.82% assessing whether specific will continue financing product only at loss 18.88%. These results shed light learning’s promising applicability marketing, vastly improve related costs efficiency.