期刊名称：International Journal of Intelligence Science
印刷版ISSN：2163-0283
电子版ISSN：2163-0356
出版年度：2012
卷号：2
期号：4A
页码：181-189
DOI：10.4236/ijis.2012.224024
出版社：Scientific Research Publishing
摘要：Personal credit scoring is the application of financial risk forecasting. It becomes an even important task as financial institutions have been experiencing serious competition and challenges. In this paper, the techniques used for credit scoring are summarized and classified and the new method—ensemble learning model is introduced. This article also discusses some problems in current study. It points out that changing the focus from static credit scoring to dynamic behavioral scoring and maximizing revenue by decreasing the Type I and Type II error are two issues in current study. It also suggested that more complex models cannot always been applied to actual situation. Therefore, how to use the assessment models widely and improve the prediction accuracy is the main task for future research.
关键词：Credit Scoring; Ensemble Learning; Dynamic Behavioral Scoring; Type I and Type II Error
