Research On Credit Risk Management Of A Rural Commercial Bank Based On Data Mining

With the explosive growth of business data of commercial banks,the importance of giving full play to the value of data is gradually highlighted.How to make good use of massive data resources has become the key to the sustainable development of commercial banks.At present,the profit of commercial banks through loan business still accounts for a large part of the total profit,so whether commercial banks can keep pace with the times,improve the credit risk management process and enhance the ability of credit risk prevention and control by fully mining data resources and effectively reduce the non-performing loan rate,so as to continuously improve the level of profitability is the top priority of the development of commercial banks.On the basis of summarizing the theory of bank credit risk management and data mining technology,this paper first introduces the basic situation and business development of A rural commercial bank,and emphatically analyzes the current situation and existing problems of A rural commercial bank's credit risk management.Considering that A rural commercial bank's main credit business is personal credit,this paper selects A rural commercial bank's personal credit data to build a credit risk prediction model,including: selecting 26818 personal credit business data of A rural commercial bank,using missing value processing,repeated data processing and other methods to preprocess the data,and building a credit risk prediction model based on decision tree algorithm.The effectiveness of the model is verified by the evaluation of the model.Finally,combined with the analysis results,this paper discusses the credit risk prevention and control strategy of A rural commercial bank.