The embodiment of the present description provides a method and device for determining consumer financial default risk. According to one mode of execution for the method, different models based on recurrent neural networks are respectively used to process short-term operation sequences and long-term behavior data set sequences of a consumer, so as to perform risk assessment of the consumer; and at least two different processing results are comprehensively handled, so as to obtain a result of consumer financial default risk. In this way, on the one hand, deeper time-series data can be used; and on the other hand, the final result can be comprehensively determined through the output results of a plurality of models. The mode of execution can improve the validity of determining consumer financial default risk.
METHOD AND DEVICE FOR DETERMINING CONSUMER FINANCIAL DEFAULT RISK