Credit risk classification and prediction based on deep neural network algorithm

HIGHLIGHTS

• What: The results of the study show that the occurrence of default by a user is positively correlated with age family years of employment and credit length and negatively correlated with income amount rate status and percentage of income. The results of this study show that the established model has high reliability and accuracy in accurately predicting whether a user has defaulted or not which provides an important reference for risk assessment and decision-making. On the dataset division, the dataset is divided into training set and test set according to the ratio of 7:3, the . . .
  

   

  

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