OPTIMIZATION OF ATM AND BRANCH CASH OPERATIONS USING AN INTEGRATED CASH REQUIREMENT FORECASTING AND CASH OPTIMIZATION MODEL
Published 2018-04-25
How to Cite
How to Cite
Abstract
In this study, an integrated cash requirement forecasting and cash inventory optimization model is implemented in both the branch and automated teller machine (ATM) networks of a mid-sized bank in Turkey to optimize the bank’s cash supply chain. The implemented model’s objective is to minimize the idle cash levels at both branches and ATMs without decreasing the customer service level (CSL) by providing the correct amount of cash at the correct location and time. To the best of our knowledge, the model is the first integrated model in the literature to be applied to both ATMs and branches simultaneously. The results demonstrated that the integrated model dramatically decreased the idle cash levels at both branches and ATMs without degrading the availability of cash and hence customer satisfaction. An in-depth analysis of the results also indicated that the results were more remarkable for branches. The results also demonstrated that the utilization of various seasonal indices plays a very critical role in the forecasting of cash requirements for a bank. Another unique feature of the study is that the model is the first to include the recycling feature of ATMs. The results demonstrated that as a result of the inclusion of the deliberate seasonal indices in the forecasting model, the integrated cash optimization models can be used to estimate the cash requirements of recycling ATMs.
References
- Agoston, K. C., Benedek, G., & Gilanyi, Z. (2016). Pareto improvement and joint cash management optimisation for banks and cash-in-transit firms. European Journal of Operational Research 254 (3), 1074 - 1082.
- Baker, T., Jayaraman, V., & Ashley, N. (2013). A Data‐Driven Inventory Control Policy for Cash Logistics Operations: An Exploratory Case Study Application at a Financial Institution. Decision Sciences 44 (1), 205 - 226.
- Baumol, W. J. (1952). The Transactions Demand for Cash: An Inventory Theoretic Approach. The Quarterly Journal of Economics 66 (4), 545 - 556.
- Bretnall, A. R., Crowder, M. J., & Hand, D. J. (2010). Predictive-sequential forecasting system development for cash machine stocking. International Journal of Forecasting 26, 764 - 776.
- Castro, J. (2009). A Stochastic Programming Approach to Cash Management in Banking. European Journal of Operational Research 192 (3), 963 - 974.
- Ekinci, Y., Lu, J.-C., & Duman, E. (2015). Optimization of ATM cash replenishment with group-demand forecasts. Expert Systems with Applications 42 (7), 3480 - 3490.
- Eppen, G. D., & Fama, E. F. (1968). Solutions for Cash-Balance and Simple Dynamic-Portfolio Problems. The Journal of Business 41 (1), 94 - 112.
- Geismar, H. N., Sriskandarajah, C., & Zhu, Y. (2017). A Review of Operational Issues in Managing Physical Currency Supply Chains. Production and Operations Management 26 (6), 976 - 996.
- Lazaro, J. L., Jimenez, A. B., & Takeda, A. (2018). Improving cash logistics in bank branches by coupling machine learning and robust optimization. Expert Systems With Applications 92, 236 - 255.
- Osorio, A. F., & Toro, H. H. (2012). An MIP model to optimize a Colombian cash supply chain. International Transactions in Operational Research 19 (5), 659 - 673.
- Simutis, R., Dilijonas, D., Bastina, L., Friman, J., & Drobinov, P. (2007). Optimization of Cash Management for ATM Network. Information Technology and Control 36 (1A), 117 - 121.
- Teddy, S. D., & Ng, S. K. (2011). Forecasting ATM cash demands using a local learning model of cerebellar associative memory network. International Journal of Forecasting 27 (3), 760 - 776.
- Tobin, J. (1956). The interest elasticity of transactions demand for cash. The Review of Economics and Statistics 38 (3), 241 - 247.
- Venkatesh, K., Vadlamani, R., Prinzie, A., & Van del Poen, D. (2014). Cash demand forecasting in ATMs by clustering and neural networks. European Journal of Operational Research 232 (2), 383 - 392.