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Bank Customer Response Based on Data Mining

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DOI: 10.23977/iemb.2019.036

Author(s)

Yinbin Liu, Mimi Yu, and Ziyi Hu

Corresponding Author

Mimi Yu

ABSTRACT

The development of the era of big data has made China's banking industry face fierce external competition and huge internal limitations. Moreover, the current research on the banking industry mostly stays in the theoretical analysis, and rarely continues to quantitatively analyze the bank customer response problem. First based on the viewpoint of precision marketing, this paper reviews the research status of using data mining technology in precision marketing. Second, we use the telemarketing data of a bank in Europe in 2014, then the collected bank data is cleaned and converted, and the appropriate bank customer response model: logistic regression model is selected. Then the model is evaluated and predicted. At last, the modeling results show that the precise marketing based on data mining technology plays an important role in customer response of banking industry, and discusses the important role of precise marketing in improving marketing efficiency and reducing bank marketing costs.

KEYWORDS

date, banking house, customer respone

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