Abstract
This paper presents a two step model aimed at reducing cash management costs in a bank’s branch. First, data mining was used to forecast daily cash demand, comparing an ARMA-ARCH model with a neural network. Secondly, using the prior result, a linear programming model was solved. The optimal allocation of resources, i.e., cash collections and supplies was estimated showing that the model can be a helpful tool to support the determination of collections and supplies at the bank branch.
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Cardona, L., Moreno, L.A. Cash management cost reduction using data mining to forecast cash demand and LP to optimize resources. Memetic Comp. 4, 127–134 (2012). https://doi.org/10.1007/s12293-012-0080-4
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DOI: https://doi.org/10.1007/s12293-012-0080-4