论文标题
关于信用评分的R套餐景观的概述
An Overview on the Landscape of R Packages for Credit Scoring
论文作者
论文摘要
信用评分行业具有悠久的传统，即使用统计工具进行贷款默认概率预测，并且在机器学习炒作之前已经建立了特定的特定标准。尽管有几家商业软件公司为此目的提供了针对R显式软件包中的信用记分卡建模的特定解决方案。近年来，这发生了变化，并且已经开发了一些专门用于信用评分的软件包。本文的目的是对这些软件包进行结构化的概述。这可以指导用户为期望的目的选择适当的功能，并希望进一步有助于指导未来的开发活动。本文以随后的建模步骤形成典型的记分卡发展过程的指导。
The credit scoring industry has a long tradition of using statistical tools for loan default probability prediction and domain specific standards have been established long before the hype of machine learning. Although several commercial software companies offer specific solutions for credit scorecard modelling in R explicit packages for this purpose have been missing long time. In the recent years this has changed and several packages have been developed which are dedicated to credit scoring. The aim of this paper is to give a structured overview on these packages. This may guide users to select the appropriate functions for a desired purpose and further hopefully will contribute to directing future development activities. The paper is guided by the chain of subsequent modelling steps as they are forming the typical scorecard development process.
