Research On The Management Plan Of Smart Network Construction Of Postal Savings Bank Based On Big Data Analysis

With the acceleration of electronic and information technology,the era of big data came into being,and the transformation of traditional banking outlets was also put on the agenda in the era of big data.The post office of the Postal Savings Bank clearly stated the requirements for the intelligentization of outlets in the 2015-2017 work report.However,in actual operation,there are still unreasonable imbalances in the distribution of outlets,long queue waiting times,and high input-output ratios.Major problems affect the healthy development of smart outlets.This research will be based on the current big data accumulation of the postal savings bank’s smart network operations,through the analysis of big data,to improve the scientific management level of the postal savings bank’s smart network.The thesis focuses on the research of demand analysis,model design and empirical analysis.In terms of demand analysis,the Q County Branch of China Postal Savings Bank Co.,Ltd.conducts demand analysis from three aspects: research subject,overall demand and detailed demand,and introduces the status quo of postal savings bank smart network construction management.The bank’s smart network operation management is insufficient,and combined with the problem,the overall demand of the postal savings bank smart network based on big data analysis is determined,and the positioning and layout,service and process,operation and organization of the postal savings bank smart network based on big data analysis are determined.Three functional requirements.In terms of model design,combined with the definition of big data analysis,the process of preparing data and generating models,the overall design of the smart savings network of postal savings banks based on big data analysis,based on the research needs,simulated the Q County Branch of China Postal Savings Bank Co.,Ltd.The three-year operational data of the network in 2016-2018 has modeled three functions: positioning and layout,service and process,operation and organization.In terms of empirical analysis,based on the simulated data,based on the demand of the RFM model,the total number of customers received after the last investment in the network between 2016 and 2018 is from December 31,2018,and the capital is invested in each network in 2016-2018.In 2016-2018,the nets of all the outlets after the last investment in the capital will be standardized,and the K-means clustering analysis will be applied by SPSS21.0.At the same time,SPSS Clementine will be analyzed for data such as business type,appointment or not,counter/self-service,business processing time(seconds),waiting time(seconds)for outlet customers in 2016-2018.Based on the requirements of the RFM model,the total number of times(seconds)for the last time the customer came to the branch tohandle the business from December 31,2018,and the number of times the customer came to the outlet in 2016-2018(times),2016-2018 In the past three years,the total amount of money(yuan)processed by the customer to the outlets was standardized,and then the K-means clustering analysis was performed using SPSS21.0.According to the analysis,the postal savings bank smart network construction management plan was proposed for positioning and layout,service and process,operation and organization.