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Abstract:
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In retail banking industry, understanding exactly the characteristics and preferences of customers through statistical approaches is an effective way to improve the performance of bank branches. In order to handle the complexity of data, in this paper we present multi-dimensional statistical analysis from diverse perspectives of banking customers, including demographic characteristics, transaction behavior and regional effects. Firstly, customer segmentation process is implemented by multi-dimensional clustering analysis. Statistical test procedures are then employed to mine the characteristics of various customer segments. Finally regression analysis is presented to forecast business trends of potential customers. The analysis is based on the data of one of the largest banks in China, and the results show the high potential of the study for practices in retail banking industry.
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