A method and device for assessing financial default risk of a user. The method comprises: first obtaining a plurality of short-period fine-grained data sets comprising various amount information and merchant information related to the borrowing behaviors of the user, processing the data sets by using a recurrent neural network to obtain the intermediate processing result; obtaining coarse-grained statistical information of the user in the long period to serve as the breadth feature, and further processing the statistical information and the obtained intermediate processing result by using a fully-connected deep neural network, so that final financial risk assessment is carried out. The device corresponds to the method. In this case, the financial default risk is better accessed by combining the depth features and the breadth features.
METHOD AND DEVICE FOR ASSESSING FINANCIAL DEFAULT RISK