INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGIES

FORECASTING EXPECTED BANK LOSSES AT GRANTING A LOAN

Authors

  • Bulantayev A.M. International Information Technology University
  • Musakhan K.B. International Information Technology University
  • Moldagulova A.N. International Information Technology University
  • Sembina G.K. International Information Technology University

DOI:

https://doi.org/10.54309/IJICT.2021.05.1.019

Keywords:

component, data analysis, credit risk, Loss Given Default, Expected Loss, Probability of Default, Exposure at Default, logistic regression, model, non-performing loans, Special Air Service platform, forecasting

Abstract

This article uses the sample data of the SAS platform as an example to introduce the statisti-cal analysis and prediction of the expected loss of loans issued by banks. The original data for this study comes from a Kaggle source, which provides information about the credit history of bank customers. The technology is based on logistic regression, graphical data analysis, and the basis of building a model on the SAS platform. The model can be used to predict credit risk and describe credit risk in the banking system.

Downloads

Download data is not yet available.

Downloads

Published

2021-03-15

How to Cite

Bulantayev A.M., Musakhan K.B., Moldagulova A.N., & Sembina G.K. (2021). FORECASTING EXPECTED BANK LOSSES AT GRANTING A LOAN. INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGIES, 2(1), 145–149. https://doi.org/10.54309/IJICT.2021.05.1.019

Issue

Vol. 2 No. 1 (2021): INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGIES

Section

Статьи

License

Copyright (c) 2021 International Journal of Information and Communication Technologies

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

https://creativecommons.org/licenses/by-nc-nd/3.0/deed.en

Most read articles by the same author(s)