基于数据挖掘的金融服务信用评分系统

Adel Hassan, Rashid Jayousi
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引用次数: 0

摘要

大多数金融服务机构(尤其是银行业)用于对其基于客户的授予风险方法进行分类的信用评分程序。本文中讨论的贷款类型可能因银行而异,如住房贷款、汽车贷款或个人贷款。此外,本文还讨论了一种不同的评分方法,并将基于贷款的评分水平分为好贷款和坏贷款。将使用各种数据挖掘技术来分析和评估这些贷款,使银行能够以最小的风险向客户发放贷款,这些客户可以根据银行与其客户之间预定义的和经批准的协议支付贷款。数据挖掘技术及其与信用评分系统的问题将通过使用数据挖掘技术和信用评分技术的实验来涵盖,使用统计和高级技术,通过选择银行信贷数据集进行培训和测试。
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Financial Services Credit Scoring System Using Data Mining
Credit scoring procedures used by most financial services organizations, especially the banking sector to classify their customers-based granting risk methodology. Loans types discussed in this paper can vary from bank to bank and such as housing loans, cars loans, or personal loans. Moreover, this article discussed a different kind of scoring approaches and categorized loans-based scoring level to be good loans or bad loans. Various data mining techniques will be used to analyses and evaluate these loans to enable the bank to grant the loans with minimum risk to the customer that can pay for the loan based on a predefined and approved agreement between the bank and its customers. Data mining techniques and their issues with credit scoring systems will be covered through experiments using data mining techniques and credit scoring techniques using both statistical and advanced techniques by chosen bank credits loans data set for training and testing set.
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