论文标题
通过RFM模型和无监督的机器学习对银行客户进行细分
Segmenting Bank Customers via RFM Model and Unsupervised Machine Learning
论文作者
论文摘要
近年来，金融机构面临的主要挑战之一是使用可靠和有利可图的细分的新方法保留客户。在银行领域，向所有现有客户提供所有服务的方法并不总是可行。但是，要意识到要出售的东西，何时出售以及销售谁，对响应新服务和购买新产品的客户的转换率有很大的变化。在本文中，我们使用了RFM技术和各种聚类算法应用于阿塞拜疆最大的私人银行之一的真实客户数据。
In recent years, one of the major challenges for financial institutions is the retention of their customers using new methodologies of reliable and profitable segmentation. In the field of banking, the approach of offering all of the services to all the existing customers at the same time does not always work. However, being aware of what to sell, when to sell and whom to sell makes a huge difference in the conversion rate of the customers responding to new services and buying new products. In this paper, we used RFM technique and various clustering algorithms applied to the real customer data of one of the largest private banks of Azerbaijan.
