决策树ID3算法在银行信贷业务中的应用

银行信贷业务是银行的一项重要业务,该业务存在一定的风险,如果我们能够预测客户的违约风险就可以最大程度的降低风险。数据挖掘技术可以很好的解决这一问题。将数据挖掘技术运用到银行客户信用评估,在庞大的数据中将看似无关联的数据进行筛选和净化,提取出有价值的信息,对客户贷款申请做出恰当的回应。数据挖掘是信息技术发展的必然结果,它是指通过挖掘算法从大量数据中抽取挖掘出隐含在其中的有价值的模式或规律等信息的复杂过程。其中,对数据的分类是数据挖掘领域研究的重要课题。本文通过决策树的经典算法ID3算法对银行信贷业务进行分析,并总结了该算法相对于其他算法的优缺点。     

ID3分类算法在银行客户流失中的应用研究

决策树已被成功应用到许多分类问题上,其中ID3是决策树学习的典型算法.文中就该算法在银行客户流失中的应用做了实例研究.叙述了ID3分类算法的原理及其实现算法,并分析了银行客户流失的原因和分类,以一个具体案例详细讲解了ID3分类算法在银行客户流失分析的具体应用流程,包括:数据采样、数据分析、建立模型和模型解释.文中实现ID3算法并作用于银行数据得到一个银行客户流失模型,通过提取模型中的规则对银行预测客户流失特征具有一定的辅助作用.     

基于决策树的银行客户分类应用研究

当今国内银行面临着巨大的压力和挑战,零售银行是目前中国银行业的一项关键业务。银行的重点是做好市场客户细分,有效挖掘客户需求,提供客户差异化服务。本文结合太仓农村商业银行的内测数据,对客户分类,然后基于决策树数据挖掘技术C4.5算法画出决策树,得到客户分类规则。     

商业智能BI在银行信贷决策中的应用

根据银行业多年来的信贷记录,运用决策树算法进行建模、分类,从而构造出一棵决策树来帮助银行决策。决策树具有自学习能力,随着业务经验的积累,模型的再训练,其决策精度将会不断提高。     

基于改进的代价敏感决策树的网络贷款分类

在网络贷款用户数据集中，贷款成功和贷款失败的用户数量存在着严重的不平衡，传统的机器学习算法在解决该类问题时注重整体分类正确率，导致贷款成功用户的预测精度较低。针对此问题，在代价敏感决策树敏感函数的计算中加入类分布，以减弱正负样本数量对误分类代价的影响，构建改进的代价敏感决策树；以该决策树作为基分类器并以分类准确度作为衡量标准选择表现较好的基分类器，将它们与最后阶段生成的分类器集成得到最终的分类器。实验结果表明，与已有的常用于解决此类问题的算法（如MetaCost算法、代价敏感决策树、AdaCost算法等）相比，改进的代价敏感决策树对网络贷款用户分类可以降低总体的误分类错误率，具有更强的泛化能力。     

一种新型的模型树算法研究及应用

决策树算法训练速度快、结果易于解释,但在实际应用中其分类精度难以满足业务要求。为了提高决策树算法的精度,基于LogitBoost算法的优点,对决策树C4.5算法进行了改进。在决策树的叶节点上应用LogitBoost算法建立叠加回归模型,得到一种新型的模型树算法-LCTree算法。通过11组UCI数据集试验,经分析比较,证明LCTree算法比其他算法更有效。将该算法应用于电信客户离网预警系统建模,结果表明,该算法可有效地分析客户特征,精确地预测离网客户。     

数据仓库和数据挖掘在信用社客户关系管理中的应用

中国的信用合作联社作为中国银行业的唯一的在广大农村地区生存的银行机构,成为我国银行业的弱势群体,其更应该加快利用先进的科学的管理方法去生存和发展。本文主要介绍信用社数据仓库如何建立及决策树在信用社客户关系管理中的应用,用双重样本对决策树进行训练、修剪,并用修剪后决策树对信用社客户预测分类,准确率达到百分之七十。     

聚类算法在银行客户细分中的应用

针对聚类算法在金融领域广泛应用的实际情况,基于银行客户数据集,对DBSCAN, K-means和X-means 3种聚类算法在执行效率、可扩展性、异常点检测能力等方面进行对比分析,并提出将X-means算法应用于银行业客户细分。利用X-means算法建立了一套银行客户细分模型,为银行决策者提供科学的决策支持。     

基于逻辑斯谛回归的银行营销

近年来,随着科技和经济水平的快速发展,企业营销策略变得多样化,在互联网飞速发展、人工智能技术越来越普遍的今天,亲力亲为的传统营销目标客户的调查方式已逐渐退出历史舞台,而利用人工智能机器学习对受众客户进行分析与预测变得越来越广泛。本文利用逻辑斯谛回归机器学习算法,以客户的基本资料和银行推销行为相关数据为特征,在以往的数据中分析潜在贷款订购客户数据,实现对该客户是否会订购银行定期存款项目的辅助判断,帮助银行进行营销广告的精准投放,从而减小人工出错的几率并缩短预算的时间,最终提高银行效率。     

数据挖掘技术下的银行客户流失决策树预测算法

在银行客户流失预测系统中经常要通过客户数据对未知客户的服务信息进行预测,以对银行今后的经营策略提供依据。在对客户的预测中,经常需要对他们的某种分类属性进行分类规则挖掘。该文主要探讨使用决策树这种常用的有效的方法来对客户数据进行分类规则挖掘。     

基于AP聚类与随机森林的客户流失预测研究

利率市场化、大数据迅速发展,银行业均表现出明显的"二八定律"现象,20％的优质客户占据了银行的大部分资产.那么,如何防止银行客户流失,尤其是优质客户的流失,已经成为银行越来越关注的问题.因此,建立优质客户流失预警模型就显得尤为重要.以某商业银行为例,重新对客户流失进行定义,重点关注银行优质客户的流失预警,首先使用AP聚...     

分类算法及其在电信客户保持的应用

由于电信市场竞争日益激烈,为了保持客户,防止客户流失,提升企业的竞争力,利用DBSCAN算法对流失客户群数据进行划分,分析客户流失原因,结合决策树ID3算法进行客户流失预测,实验结果表明,两种算法的结合,使得客户流失预测准确率得到较大提高.     

决策树方法在煤炭物流客户分析中的应用

目前物流企业中积累了大量的客户历史数据,为了有效利用这些数据,使用数据挖掘方法对客户进行分类管理和服务是CRM中非常重要的一方面。而决策树是进行分类分析与数据挖掘的常用方法。研究了运用C4.5算法对煤炭物流客户信息构造决策树,并把提取到的规则应用到公路煤炭物流公司的客户关系管理中,结果证明具有较好的应用价值。     

Pythagorean fuzzy VIKOR approaches based on TODIM for evaluating internet banking website quality of Ghanaian banking industry

With the rapid development of Internet banking technology in Ghana, the website quality evaluation is the essential core of the customer, which is regarded as a multi-criteria decision making (MCDM) problem. Due to the uncertainty of Internet banking, the evaluation of criteria may be measured by Pythagorean fuzzy numbers (PFNs). In addition, the customer usually does not exhibit complete rationality in the decision procedure. Based on the traditional VIKOR (Vise Kriterijumska Optimizacija I Kompromisno Resenje) method of MCDM, this paper provides a new perspective of a compromised solution, which can handle the decision maker’s psychological behavior by inducing TODIM (a Portuguese acronym meaning Interactive Multi-Criteria Decision Making). By defining Pythagorean fuzzy entropy and cross-entropy measures, we study the determination of the weights of the criteria in advance. Then, considering the psychological behavior of the customer, we design two types of strategies for the combination between TODIM and VIKOR. Meanwhile, the corresponding methods have been developed, i.e., Approaches I and II. After that, a simulated example of ranking Internet banking websites in the Ghanaian banking industry is given to illustrate the validity and applicability of our proposed approaches. Finally, we utilize the Wilcoxon signed-rank test and then discuss the differences among VIKOR, TODIM and our proposed methods.     

E-banking: challenges and opportunities in the Greek banking sector

Internet technologies have a great potential for changing fundamentally the banks and the banking industry. The opportunities, which the e-banking services and technologies offer to the banking sector in order to fulfil existing customer needs and to attract new prospective customers, are the driving forces for banks in order to design, develop and operate their own e-banking systems. This paper examines the challenges and opportunities of e-banking for the Greek banking sector, during the e-commerce era, and also presents the results of a survey of banking executives working at banks offering e-banking services. The main findings demonstrate that banks expand to e-banking services in order to remain competitive, to keep track with technological developments and to benefit from the lower cost of e-banking transactions. The major problems they face are the low response rate from customers and the implementation of security and data protection mechanisms. The relatively low Internet usage, the non-familiarity with technologically advanced devices and problems regarding security and privacy are the main factors that have a negative influence on the adoption of e-banking services by customers in Greece.     

FCM-based customer expectation-driven service dispatch system

Maintaining long-term customer loyalty has been an important issue in the service industry. Although customer satisfaction can be enhanced with better service quality, delivering appropriate services to customers poses challenges to service providers, particularly in real-time and resource-limited dynamic service contexts. However, customer expectation management has been regarded as an effective way for helping service providers achieve high customer satisfaction in the real world that is nevertheless less real-time and dynamic. This study designs a FCM-based customer expectation-driven service dispatch system to empower providers with the capability to deal effectively with the problem of delivering right services to right customers in right contexts. Our evaluation results show that service providers can make appropriate decisions on service dispatch for customers by effectively managing customer expectations and arranging their contextual limited resources and time via the proposed service dispatch system. Meanwhile, customers can receive suitable service and obtain high satisfaction when appropriate services are provided. Accordingly, a high-performance ecosystem can be established by both service providers and customers who co-create value in the dynamic service contexts.     

A hybrid approach to integrate genetic algorithm into dual scoring model in enhancing the performance of credit scoring model

Credit scoring model is an important tool for assessing risks in financial industry, consequently the majority of financial institutions actively develops credit scoring model on the credit approval assessment of new customers and the credit risk management of existing customers. Nonetheless, most past researches used the one-dimensional credit scoring model to measure customer risk. In this study, we select important variables by genetic algorithm (GA) to combine the bank’s internal behavioral scoring model with the external credit bureau scoring model to construct the dual scoring model for credit risk management of mortgage accounts. It undergoes more accurate risk judgment and segmentation to further discover the parts which are required to be enhanced in management or control from mortgage portfolio. The results show that the predictive ability of the dual scoring model outperforms both one-dimensional behavioral scoring model and credit bureau scoring model. Moreover, this study proposes credit strategies such as on-lending retaining and collection actions for corresponding customers in order to contribute benefits to the practice of banking credit.     

Technology adoption: A conjoint analysis of consumers׳ preference on future online banking services

The importance of service delivery technology and online service adoption and usage in the banking industry has received an increased discussion in the literature in recent years. Owing to the fact that Strong online banking services are important drivers for bank performance and customer service delivery; several studies have been carried out on online banking service adoption or acceptance where services are already deployed and on the factors that influence customers׳ adoption and use or intention to use those services. However, despite the increasing discussion in the literatures, no attempt has been made to look at consumers׳ preference in terms of future online banking service adoption. This study used conjoint analysis and stated preference methods with discrete choice model to analyze the technology adoption pattern regarding consumers׳ preference for potential future online banking services in the Nigerian banking industry. The result revealed that to increase efficiency and strengthen competitiveness, banks need to promote smart and practical branded services especially self-services at the same time promote a universal adoption of e-banking system services that add entertainment or extra convenience to customers such as ease of usage including digital wallet, real-time interaction (video banking), ATMs integrated with smart phones, website customization, biometric services, and digital currency. These services can contribute to an increasing adoption of online services.     

决策树技术在医院住院客户划分中的应用

本文以省妇幼保健院历史的住院业务数据为样本,通过数据挖掘的决策树建模方法建立其住院客户的划分模型,得到分类规则,在此基础上将住院客户划分为不同的群体。通过对客户的划分及其特征分析,医院可清楚的了解重点客户并给予重点客户群体以按需要定制的个性化服务,这将极大提升这部分客户的忠诚度和满意度,从而确保医院主流利润和收入来源的长期性和稳定性。