Analysis of Digital Transformation with Random Neural Network Algorithm in Commercial Bank

Focusing on the digital transformation of commercial bank, and basing on the case data produced by the digital transformation project, the factors analysis is conducted to explain commercial bank digital transformation. Specifically, by analyzing the 73,555 daily interaction data from the digital project, the text analysis algorithm is applied to get interaction content feature, interaction emotion feature, and interaction experience feature. In order to get the most important features, a random neural network algorithm is employed to get the optimal feature subset. Finally, the feature analysis experiment is constructed to explain the connection between the user's interaction and bank digital transformation. The analysis results provide the management insights for the commercial bank on the digital transformation project application.