The invention relates to an SVM-based power consumer credit risk early warning method and system, and the method comprises the steps: setting a threshold value for a power consumer credit risk basic index, and dividing risk early warning intervals of different power consumer credit risk basic indexes according to the threshold value; selecting sample data, processing the sample data, distributingcorresponding weights to the power consumer credit risk basic indexes by using a principal component analysis method, calculating a risk early warning evaluation value of the sample data, and dividingrisk categories where the risk early warning evaluation value is located according to the risk early warning evaluation value; establishing a power consumer credit risk early warning SVM model, and predicting the power consumer credit risk; and taking the obtained optimal parameter value as a parameter value of a power consumer credit risk early warning SVM model, and optimizing the power consumer credit risk early warning SVM model. According to the method, parameter optimization is carried out through the SVM classification model, the prediction accuracy for the nonlinear relationship and the small sample model is high, and a good early warning effect is achieved in credit risk early warning.