首页    期刊浏览 2024年12月02日 星期一
登录注册

文章基本信息

  • 标题:Predicting take-up of home loan offers using tree-based ensemble models: A South African case study
  • 本地全文:下载
  • 作者:Tanja Verster ; Samistha Harcharan ; Lizette Bezuidenhout
  • 期刊名称:South African Journal of Science
  • 印刷版ISSN:0038-2353
  • 电子版ISSN:1996-7489
  • 出版年度:2021
  • 卷号:117
  • 期号:1-2
  • 页码:1-8
  • DOI:10.17159/sajs.2021/7607
  • 语种:English
  • 出版社:The Foundation for Research Development
  • 摘要:We investigated different take-up rates of home loans in cases in which banks offered different interest rates.If a bank can increase its take-up rates, it could possibly improve its market share.In this article, we explore empirical home loan price elasticity, the effect of loan-to-value on the responsiveness of home loan customers and whether it is possible to predict home loan take-up rates.We employed different regression models to predict take-up rates, and tree-based ensemble models (bagging and boosting) were found to outperform logistic regression models on a South African home loan data set.The outcome of the study is that the higher the interest rate offered, the lower the take-up rate (as was expected).In addition, the higher the loan-to-value offered, the higher the take-up rate (but to a much lesser extent than the interest rate).Models were constructed to estimate take-up rates, with various modelling techniques achieving validation Gini values of up to 46.7%.Banks could use these models to positively influence their market share and profitability.
  • 关键词:pricing;retail;credit risk;boosting;bagging;price elasticity
国家哲学社会科学文献中心版权所有