A Two-Stage Cardholder Behavioral scoring Model Using Artificial Neural Networks and data Envelopment Analysis
學年 99
學期 2
出版（發表）日期 2011-03-01
作品名稱 A Two-Stage Cardholder Behavioral scoring Model Using Artificial Neural Networks and data Envelopment Analysis
作品名稱（其他語言）
著者 I-Fei Chen
單位 管理科學學系暨研究所
出版者
著錄名稱、卷期、頁數 International Journal of Advancements in Computing Technology 3(2)
摘要 Since the databases that banks use for analysis of cardholders’ repayment behaviours are usually large and complicated, and the extant classification techniques hardly offer 100% correct classification accuracy so as to possibly incur a considerable loss associated with type II errors, the prediction of cardholders’ future payment behaviours has been still referred to as a difficult task in the credit industry. This paper proposes a two-stage cardholder behavioural scoring model, with merits of artificial neural networks (ANNSs) and data envelopment analysis (DEA), which not only enables banks to verify the ANNSs predicted results of each cardholder’s future repayment behaviour as well as to identify creditworthy cardholders who is profitable with low risks, but also provides guidelines to improve contributions of each inefficient cardholder for card issuer profitability.
關鍵字 Chi-square Automatic Interaction Detector (CHAID);Artificial Neural Networks (ANNs);Data Envelopment Analysis (DEA);Behavioural Scoring;Data Mining
語言 en
ISSN 2005-8039;2233-9337
期刊性質 國外
收錄於
產學合作
通訊作者
審稿制度 否
國別 KOR
公開徵稿
出版型式 ,電子版,紙本
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