Model of the Forecasting Cash Withdrawals in the ATM Network

To increase the economic efficiency of the self-service devices networks operated by banks and processing companies, possibly due to the use of mathematical models and algorithms in the cash-in-transit forecasting process. In this article the issues are considered to improve the cash drawing forecast accuracy using the model for the neural networks. Special focus is on the description of data pre-processing.