Research On Optimizing The Credit Risk Control System For Small And Medium Enterprises Of China Construction Bank H Branch Based On Big Data

As an important driving force for national economic and social development,small and medium-sized enterprises are crucial for China’s economic system reform and structural adjustment.In response to internal factors such as shortage of funds and credit for small and medium-sized enterprises,as well as external environmental constraints such as the epidemic,the country has launched the "Several Measures to Assist Small and Medium sized Enterprises in Stable Growth,Structural Adjustment,and Strong Capacity".This includes strengthening financial institutions’ loan support for small and medium-sized enterprises,increasing their initial loans,credit loans,non repayable loans,and medium to long-term loans,promoting the loan repayment model,and promoting the incremental expansion of inclusive small and medium-sized enterprise loans.At the same time,encourage banking and financial institutions to develop specialized credit schemes for small and medium-sized enterprises under the premise of controllable risks,and promote a virtuous cycle between them and the industry.However,due to factors such as scale,funding,and credit,small and medium-sized enterprises are still plagued by a lack of financing channels and information asymmetry.Therefore,as an important channel for financing small and medium-sized enterprises,bank credit is facing increasing credit risks.At present,banking institutions are using highly integrated data analysis and storage technologies such as Big data,cloud computing,artificial intelligence and blockchain to improve service efficiency and management capabilities,enhance market competitiveness,and inject new impetus into the new direction and reform of the financial industry.In the credit risk control management of small and medium-sized enterprises of CCB Branch H,the Big data risk control system has not been sufficiently applied.At present,the risk control model based on the credit scoring card model,supplemented by expert experience method and customer information for comprehensive evaluation is also used.This model often has strong subjectivity and data loss issues,and is prone to misjudgment due to financial statement distortion.Therefore,how to use the existing basic data and external data,through Big data technology and analysis,optimize the credit risk control system of SMEs,establish an intelligent Big data risk control system,and cope with the current situation of SMEs’ financing difficulties and increasing credit risks need to be further explored and solved.Based on the theoretical framework of information asymmetry,comprehensive risk management and Big data risk control,this paper uses the questionnaire survey method to analyze the current situation of the credit risk control system of small and medium-sized enterprises of CCB Branch H,and finds that in the process of developing the credit business of small and medium-sized enterprises of CCB Branch H,the breadth and depth of pre loan survey is not enough,the accuracy of in loan audit rating is not enough,and the post loan management is not paid attention to;Using PCA principal component analysis and factor matrix,establish a logistic model for principal component analysis and model analysis,screen customer default situations before lending,improve risk prediction mechanism,move risk control management forward,and improve credit asset quality.The results show that the application of small and medium-sized enterprises’ Big data credit risk control system model provides more accurate and effective strategic decision-making reference for CCB Branch H to improve risk prediction mechanism,management advance and credit asset quality,and provides risk guarantee for the sustainable and healthy development of small and medium-sized enterprises in CCB Branch H.