商业银行服务呼叫中心的来电预测

Proceedings of the 10th International Conference on Computer Modeling and Simulation Pub Date : 2018-01-08 DOI:10.1145/3177457.3177498

Sirithep Chanbunkaew, W. Tharmmaphornphilas

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引用次数: 0

摘要

在本研究中，我们开发了泰国一家商业银行呼叫中心的来电预测模型。我们发现来电是非固定的。通常情况下，假期期间的电话数量较少，而每个月初和月末的电话数量较多。采用不同的时间序列模型进行月预报，提出一种基于季节模式的日预报算法。MAPE(平均绝对百分比误差)和RMSE(均方根误差)用于比较拟议的方法和银行使用的当前模型。结果表明，该方法优于现有模型。MAPE从9.79%降低到8.12%，RMSE从960.37降低到861.88。

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Forecasting of Incoming Calls in a Commercial Bank Service Call Center

In this study, we develop forecast models for incoming calls at a call center of a commercial bank in Thailand. We found that incoming calls are non-stationary. Normally, the number of calls is low during holiday and high during the beginning and ending of each month. Various time series models are applied for monthly forecast and an algorithm based on seasonal pattern is proposed for daily forecast. MAPE (Mean Absolute Percentage Error) and RMSE (Root Mean Square Error) are used for comparing the proposed methodology and the current model that the bank uses. The results show that the proposed methodology is better than the current model. MAPE reduces from 9.79% to 8.12% and RMSE reduces from 960.37 to 861.88.

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Proceedings of the 10th International Conference on Computer Modeling and Simulation

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