The invention provides a credit scoring method, a system, a computer device and a readable medium. In a data acquisition stage, multi-channel information, such as operator information, credit card information and debit card information, is selected, and various aspects of information of a user are comprehensively considered, so that the prediction effect and stability of the model can be enhanced.Derived fields based on time slices can extract the information with real prediction value, and also can increase the prediction effect of the model. In the data preparation phase, the variables withhigh missing rate and the variables with difficult-to-interpret level are deleted, which enhances the stability of the whole model. In the model development phase, the variables with multicollinearity are deleted, which enhances the stability of the model. LASSO and other machine learning methods are used to select the variables with real prediction ability, which improves the prediction abilityof the final model.