Research on Internet financial risk early warning based on a CNN-LSTM model

Inhalt:
In order to enhance the risk control ability in the field of Internet finance, guarantee the sustainable development of the Internet finance industry, and reduce the losses brought to the Internet finance platform by unexpected events arising from personal credit, the article conducts early warning research on the credit risk in Internet finance risk based on a CNN-LSTM model, which performs extraction of deep features while predicting time series features from the user's behavioral features to collect the user's credit degree, evaluate and predict the user's credit risk, and conduct timely risk warning to prevent the expected default of personal loans, overdue repayment and other defaults. The results show that the CNN-LSTM model has good financial risk early warning effect, and can effectively take advantage of information resources to reduce the risk of Internet finance.