Predicting and analyzing long-term deposit possibility leveraging logistic regression and visual analysis

Abstract

Keeping balanced deposits in commercial banks is of great importance for the rational use of money. This article focuses on logistic regression to forecast the long-term deposit activity of banks. And the visual analysis is helpful to reveal a strong association between people's likelihood of long-term deposits and their age and happiness. In detail, people are less likely to make long-term deposits after the age of 65, i.e., after the age of retirement. In addition, people are more likely to make long-term savings when they have a high life expectancy index, such as when they are married. Finally, the whole logistic regression model is analyzed by using precision, recall, and f1-score. It is concluded that this logistic regression model is very accurate in predicting the long-term deposits of bank customers. However, the concluding section also explores the idea that the overall logistic regression model should use a broader data set for its effectiveness and high accuracy.