CREDIT RISK MODELLING FOR INDIAN DEBT SECURITIES USING MACHINE LEARNING

Authors

Charumathi Balakrishnan, Pondicherry University, IndiaFollow
Mangaiyarkarasi Thiagarajan, Vels Institute of Science, Technology & Advanced Studies, IndiaFollow

Document Type

Article

Abstract

We develop a new credit risk model for Indian debt securities rated by major credit rating agencies in India using the ordinal logistic regression (OLR). The robustness of the model is tested by comparing it with classical models available for ratings prediction. We improved the model’s accuracy by using machine learning techniques, such as the artificial neural networks (ANN), support vector machines (SVM) and random forest (RF). We found that the accuracy of our model has improved from 68% using OLR to 82% when using ANN and above 90% when using SVM and RF.

Recommended Citation

Balakrishnan, Charumathi and Thiagarajan, Mangaiyarkarasi (2021) "CREDIT RISK MODELLING FOR INDIAN DEBT SECURITIES USING MACHINE LEARNING," Bulletin of Monetary Economics and Banking: Vol. 24: No. 0, Article 6.
DOI: https://doi.org/10.21098/bemp.v24i0.1401
Available at: https://bulletin.bmeb-bi.org/bmeb/vol24/iss0/6

First Page

107

Last Page

128

Creative Commons License

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

Country

India

Affiliation

Pondicherry University