Study On Evaluation And Prediction Of Credit Environment Carrying Capacity Of County Rural Commercial Banks

Credit loan,especially policy credit loan,is an important loan business undertaken by County Rural Commercial Banks and faces high default risk.Starting from the financial integrity environment in which the county rural commercial banks are located and their own resource endowments,it is of great practical significance in today’s increasingly complex social and economic forms to establish relevant evaluation and prediction index systems,analyze their financial risk carrying capacity in a specific environment and achieve the goal of sustainable and sound development.This study selects a rural commercial bank within the jurisdiction of Qingzhen City,which has a good effect in promoting the construction of integrity and has a great impact on the county rural financial institutions,as the research object.After collecting and analyzing the sample data,and referring to the method of dividing and designing the index system commonly used in the existing literature on resource and environment carrying capacity,the various indicators are divided into four influencing index systems: objective support,regulatory support,social population and economic pressure,and non-performing asset pressure for comprehensive consideration,and then the entropy weight method and principal component analysis technology are used to complete the screening and weight calculation of the indicators,Finally,the evaluation value of the integrity environmental carrying capacity of the sample data is obtained.In the process of evaluation,it makes a detailed comment on the actual situation and business development of the sample secondary sub branches,striving to make the empirical research supported by the theoretical basis,and the conclusions of the empirical research can provide a reliable basis for the theoretical basis.In this study,the relevant knowledge of machine learning is combined to bring the evaluation results of the credit environment carrying capacity into the standard linear regression science library provided by Python’s scikit learn.Through supervised learning,the machine can automatically find out the rules in the sample data of this study,and finally obtain the credit environment carrying capacity evaluation and prediction model after the research fitting and training in this paper.On this basis,from the county rural commercial banks can achieve the goal of long-term stable and sustainable development,combined with the research conclusions,this paper puts forward reference suggestions.