Risk Measurement of the Financial Credit Industry Driven by Data

The risk measurement of financial credit industry is an important research issue in the field assessment. design algorithm can help investors avoid greater risks and obtain higher returns, so as to promote benign development industry. Based on combined deep learning algorithm, this paper studies industry, proposes a fusion auto-encoder (DAE) Long Short-Term Memory (LSTM) network. recombines value fixed features by using unsupervised mechanism DAE, extracts non for with memory characteristics LSTM experimental results show that: compared single generalized regression neural network network, average accuracy DAE-LSTM improved about 6.49% 3.25% respectively, which has better application effect measurement.