Study On The Post-loan Collection Strategy For Customers Applying For The Credit Card Online Of S Bank

Credit card business develops rapidly in our country,and along with the popularity of 4G,the card issuing mode of banks has been changed dramatically.All banks in China began to arrange online application functions around 2013,and at present,applying for credit cards through online channels has become the main way for banks to gain customers.The collection strategy studied in this paper is the macroscopic way and method for banks managing overdue assets after the loan,which mainly solves the problems of three aspects,including the collection order,collection method and effect improvement.The effect of the collection strategy significantly affects new nonperforming loans of banks,and then affects profits of banks.However,along with the significant changes in group characteristics of online application customers,the post-loan collection strategy of banks in the early stage is gradually not suitable for online application customers.This paper explores risk characteristics of online customers that are different from those of previous offline customers through the analysis and research on the causes of credit risk and the means of asset disposaland then studies the risk performance of online customers and the causes of risk performance.Then this paper takes newly increased overdue customers of S Bank as the objects,and conducts analysis and verification by using Logistic regression model for exploring the customer classification dimension,setting up the model to classify and hierarchically manage customers,and putting forward the post-loan collection strategy for online application customers based on the accurate customer classification,which will be made verification.The following conclusions are drawn through the research which is taking S Bank as an object: First of all,there are significant differences among customers of different card issuing channels,and the collection for customers of online application channels is more difficult.Then,there are three conclusions according to the results of Logistic regression.Firstly,there is a negative correlation between the card grade,age and number of stages of customers after the deadline and the collection effect.Secondly,there is a positive correlation between the overdue principal and educational background of customers after the deadline and the collection effect.Thirdly,from the condition of debts – income,the order of probability of successful collection is: customers with “high debts and low income” < customers with “low debts and low income” < customers with “high debts and high income” < customers with “low debts and high income”.Lastly,the 90-day delay rate of online application customers of S Bank is reduced 4.42 percentage points and the collection effect is increased by 15.94% after implementing optimized strategy.The research practice verifies that the establishment of a post-loan collection strategy system based on the customer classification by establishing a model,can effectively improve the post-loan collection effect and provide the reference for the bank customer management and the post-loan asset collection under the internet mode,in which the postloan collection strategy system is establishing the early-warning disposal system and the recovery process of lost customer information,establishing value-oriented customer assistance policies and standardized collection strategies,and optimizing post-loan team evaluation and incentive strategies.