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.

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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

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