Research on Credit Loan Rating Based on LightGBM Algorithm

To meet the demand of customer credit scoring in the loan market, the paper uses machine learning algorithm to build a credit scoring model based on the collected credit data of a region to predict the customer's lending risk level. Firstly, data cleaning and exploratory analysis were carried out to obtain complete standby credit loan data; Secondly, Pearson correlation analysis and thermodynamic diagram are used to select and process characteristic independent variables and dependent variables; Finally, LightGBM model is used for training, and compared with many mainstream prediction algorithms. The complete algorithm model in the paper can achieve more than 97% in prediction accuracy, recall rate and F-1 Score evaluation index.