Sound branch cash management for less: A low-cost forecasting algorithm under uncertain demand |
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Institution: | 1. Department of Automation, Center for Brain-Inspired Computing Research, Tsinghua University, Beijing 100084, China;2. Beijing Key Laboratory of Security in Big Data Processing and Application, Beijing 100084, China |
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Abstract: | This paper deals with cash management for bank branches, under the assumption that branches have a role to play in the improvement of global bank institution performance. In the current scenario of unprecedented pressure amongst banks to keep costs under control, our contribution is the design of a sound and low-cost algorithm to optimize branch cash holdings using software implementation in SageMath. It is accompanied by data processing based on 60,000 real banking records. This is the first academic paper to run such an extensive database at branch level.We find that our algorithm by and large performs well when forecasting the cash amounts that the branch might require from the central hub to satisfy all branch necessities, avoiding the generation of either surplus or shortage of cash. It is also extremely easy to implement in daily branching practice, leading to an overall reduction in operating costs. In addition, our algorithm may be easily adjusted as required and be tailor-made to the special requirements of each banking institution. |
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Keywords: | Cash management at banking branch-level Real bank data processing Demand forecasting algorithm Stochastic processes |
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