reserve prediction, time series prediction, Long Short Time Memory (LSTM) network, date property
Reserve allocation is a significant problem faced by commercial banking businesses every day. To satisfy the cash requirement of customers and abate the vault cash pressure, commercial banks need to appropriately allocate reserves for each bank outlet. Excessive reserve would impact the revenue of bank outlets. Low reserves cannot guarantee the successful operation of bank outlets. Considering the reserve requirement is effected by the past cash balance, we deal the reserve allocation problem as a time series prediction problem, and the Long Short Time Memory (LSTM) network is adapted to solve it. In addition, the proposed LSTM prediction model regards date property, which can affect the cash balance, as a primary factor. The experiment results show that our method outperforms some existing traditional methods.
Tsinghua University Press
Yu Liu, Shuting Dong, Mingming Lu et al. LSTM Based Reserve Prediction for Bank Outlets. Tsinghua Science and Technology 2019, 24(1): 77-85.