Research On Credit Risk Of Commercial Banks Based On Data Mining Technology

With the explosion of data,the importance of making good use of data is gradually highlighted,which brings challenges to commercial Banks and good opportunities.Whether the big data of huge customers can be made good use of has become the key to risk management of commercial Banks.The profit gained by commercial Banks through lending accounts for a large part of the total profit.Therefore,whether commercial Banks can carry out scientific credit risk management and reduce bad debt rate is the key to improve the profit of commercial Banks.Traditional commercial Banks should keep pace with The Times,explore the "gold mine" of big data,improve their credit risk management level,and improve their profitability on the premise of ensuring safety.Based on the above background,this paper first introduces some basic concepts of data mining in detail.Data mining technology was formally launched in the second half of the 20 th century by integrating multiple disciplines.The main difference between data mining and statistical analysis is that although data mining has many advantages over statistical analysis,it can not be separated in data operation practice.Four kinds of data mining are introduced The mature technologies in data mining are decision tree,neural network,regression and clustering.Next,through the statistical analysis of the details of Beatles' lending,we get the lending preferences of different types of banks,and find that the main lending direction of rural commercial banks is personal credit.In response to the theme of this article,we should focus on analyzing the personal credit data of DS commercial banks.Then it analyzes the two factors that affect the bank lending,one is the policy of the central bank,the other is the commercial bank itself,which provides the theoretical basis for the following suggestions.Then it briefly introduces the basic situation,organizational structure of DS commercial bank,and analyzes the liquidity,security and profitability of DS commercial bank.With the help of Logistic model and data mining technology,and on the basis of making full use of more than 30,000 personal credit business data of DS commercial bank,this paper evaluates the personal credit default risk of commercial bank and predicts and analyzes the probability of personal credit default.This paper takes personal credit default as the research object,combines data mining technology and makes full use of Python software,establishes the personal credit default assessment model,and proposes improvement measures for the weak links in risk management of commercial Banks.