Document Type : Research Article
Authors
1
Asistant professor in Economics, Faculty of Scince, Bu-Ali Sina University, Hamedan, Iran
2
Shasta-Planning Department
3
Faculty of Management, University of Tehran,
4
Phd Student of Economic- Islamic Azad University،Science And Research Branch
5
Melli Bank of Iran -Banker
10.22084/aes.2023.27444.3564
Abstract
Abstract
Predicting deposits of a private bank by machine learning method
Abstract
In this study, based on the historical statistics of deposits of a private bank in four different categories (funds), we seek that the results and forecast of bank deposits in each category, using the methods of predicting machine learning for the first time in internal studies and comparison with the method Regression is performed. Finally, by comparing these two forecasting methods, the preference of the machine learning method is confirmed due to the study of all temporal changes in large-volume data (from the beginning to the present). Predicting the above deposit statistics for bank decision makers in the future, given the economic conditions, can be the basis for macro banking decisions. The results show that long-term, somewhat stable deposits and stable deposits will have a downward trend in the bank in the future, and unstable and profit-sensitive deposits will also have a downward trend. Gharz al-Hasna deposit has an upward trend, although it has always had fluctuations similar to sine-cosine fluctuations. It should be noted that this method of predicting machine learning is a stable method without sensitivity analysis and has high reliability.
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