The Research On Rural Commercial Bank Retail Customer Churn Based On Random Forest

With the advent of the "Internet plus" era,China’s traditional banks are facing a series of adjustments,such as the outflow of deposit funds,the lack of competitiveness in marketing products,the satisfaction of retail customers,the decline of loyalty and even the loss.The focus of inter-bank competition has gradually shifted from product to customer competition.Whoever can retain customers can retain the market and stand firm in the fierce competition market,However,the needs of customers vary with different groups of people,banks urgently need to innovate products or services and provide personalized services according to different situations of customers in the marketing process.Using big data,retail banks can effectively mine customer information and provide personalized services,so as to win customers’ favor.Compared with other banks,SRCB has been based on the rural financial market for a long time and plays an irreplaceable role in the rural financial market.The government has positioned rural commercial banks in the three rural areas,so that the bank activities at the grass-roots level,close contact with the masses,with a broad mass base,however,as the most traditional representative of traditional banks,the application of big data in all kinds of retail business is still at the exploratory stage,most of which can not meet the diversified needs of customers.Based on the above background,based on the characteristic data of customers in the whole bank of SRCB from January to June 2019,through big data analysis,this paper studies the customer’s consumption tendency and consumption mode,establish a customer segmentation model,classify the customers of the whole bank in three dimensions of loyalty,activeness and contribution,and divide the private customers into nine categories,and four kinds of customers are used as marketing target customers in the follow-up early warning model of customer churn,comprehensively and thoroughly mining the valuable laws and reasons behind customer information,and putting forward targeted marketing management opinions,which improves marketing efficiency.Through the early warning model of customer churn,we use machine learning method to learn from 15%of customers,which can identify 90%of the number of customers who have lost,greatly reduce the marketing cost and improve the efficiency of marketing retention.In a word,using the case of SRCB,this paper finds that using big data of customers to build digital customer analysis system and marketing system,and gradually realize the digital transformation of retail business,can make SRCB improve the overall efficiency...