基于动态加权组合模型的ATM现金预测方法

本文提出了一种基于动态加权组合模型的智能现金预测方法, 可以对银行ATM设备的日常现金用量进行精准预测, 为日常现金调拨管理提供决策依据. 与以往使用的单算法预测不同, 本文对银行业务、交易流水与设备等特性进行分析, 据此组合4种单一机器学习模型, 提出并实现基于动态加权组合模型的智能算法. 该算法可以为银行现金用量管理提供更智能、更精准、更高效的预测手段, 有效压降现金库存总量与回钞率, 提升现金运用率. 此方法已在广东、重庆、江西、山西、北京等地区使用, 并取得良好效果.

ATM Cash Forecasting Method Based on Dynamic Weighted Combination Model

A wise cash forecasting method based on a dynamic weighted combination model is proposed in this study, to precisely predict the daily cash consumption of ATM equipments so as to make a better decision for daily cash transfer management. Different from single-algorithm prediction used in the past, with analyzing characteristics of banking business, transaction flow, and equipment, etc., an intelligent algorithm based on a dynamic weighted combination model that combining 4 single machine learning models, is proposed and implemented in this study. This algorithm provides a more intelligent, more precise, and more efficient forecasting method for the management of bank cash consumption, effectively reduces the total amount of cash inventory and the rate of cash return, and improves the utilization rate of cash. This method has been used in Guangdong, Chongqing, Jiangxi, Shanxi, Beijing, and other areas with sound results.