Fintech Application in Banking Operations - Application of Machine Learning in Mitigating Bank Derivatives Counterparty Risks
作者: Tianshu Li
刊名: Asian Business Research, 2019, Vol.4 (3)
来源数据库: July Press
DOI: 10.20849/abr.v4i3.652
原始语种摘要: We all know that human has many psychological biases, including overconfidence, gender discrimination and so on. Although some genuine lenders may outperformance others, machine learnings have been utilized to solve this human psychological bias in many areas. By using machine learnings methods, people can make better financial decisions. This proposal tries to examine the effectiveness of several different machine learning models on predicting the ex-pose default risk, including BP neural network, decision tree, KNN, and random forest. I focus on loans on one electronic P2P lending platform, called “Paipaidai” in which lenders select and supply private loans to borrowers with different characteristics. I use machine learnings methods to predict the default risk and thus provides better...
全文获取路径: July Press 

  • machine 机器
  • platform 台地
  • select 选择
  • effectiveness 有效性
  • human 人的
  • discrimination 辨别
  • default 缺席
  • private 私有的
  • decision 决定
  • overconfidence 过于自信