Classification and Prediction of Bank Marketing Activity by Machine Learning

Abstract

As the competition in the financial industry intensifies, the customer experience has become the key to whether the financial institutions can continue to develop. As the traditional banking services are difficult to meet the needs of customers, more and more people begin to choose to trade through self-service channels or online banking. With the popularity of mobile devices, people are increasingly dependent on mobile banking and mobile payment. Banks analyze the customer behavior data to realize the effective interaction between customers and banks, which has become a hot issue in the financial industry. From the perspective of machine learning, this paper will analyze the ability of a bank customer to buy products, mainly including customer purchasing power analysis, product classification, customer stratification and other aspects. On this basis, this paper will use the decision tree algorithm to segment the customers with different purchasing power, so as to achieve precision marketing.