Abstract
Objectives: With the rise and development of Internet finance, the application of Sino US financial technology in the banking field is becoming more and more widely. Methods: In this study, for the data collection of bank customer deposits, data mining and decision tree analysis algorithms were used to classify bank customers. Results: The classification accuracy of the traditional algorithm was low, so the optimization algorithm Adaboost and the random forest improvement algorithm were proposed in this paper. The simulation effects of its application in data combination show that the classification effect of the optimization algorithm is obviously better than the traditional classification algorithm. Conclusion: The results of this study can help banks gain customers and reduce expenditures.
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