Discriminative Ability In Estimating Probability Of Default With Certain Machine Learning Algorithms Cover Image

Дискриминационна способност при оценката за вероятност от неплатежоспособност посредством някои алгоритми за машинно самообучение
Discriminative Ability In Estimating Probability Of Default With Certain Machine Learning Algorithms

Author(s): Antonio Dichev
Subject(s): Economy, Business Economy / Management
Published by: Стопанска академия »Д. А. Ценов«
Keywords: probability of default; machine learning; risk assessment; credit risk

Summary/Abstract: The article highlights the importance and added value of some machine learning algorithms in assessing default probability. The results of the research highlight the discriminative ability added to many other essential aspects of machine learning in assessing credit risk. These aspects can be identified as specific opportunities and challenges. As for the discriminative ability regarding the analysed sample, the results prove the superiority of machine learning over the traditionally established and known models. For individual business organizations with exposures to credit risk, machine learning could contribute to reducing the credit losses with larger volumes of business transactions.

  • Issue Year: 2023
  • Issue No: 4
  • Page Range: 17-30
  • Page Count: 14
  • Language: Bulgarian
Toggle Accessibility Mode