Bankruptcy Prediction of Manufacturing Companies of India Post-IBC : A Comparative Study Between Various Predictive Techniques

Authors

  •   Simrat Kaur Research Scholar, Amity University Noida, Noida - 201 313, Uttar Pradesh
  •   Adarsh Arora Professor, Amity University Noida, Noida - 201 313, Uttar Pradesh
  •   Anil Kumar Goyal Associate Professor, Maharaja Agrasen Institute of Management Studies, Rohini, New Delhi - 110 086
  •   Anjali Munde Assistant Professor, Southampton Malaysia Business School, University of Southampton

DOI:

https://doi.org/10.17010/ijf/2024/v18i3/173615

Keywords:

Random Forest

, Decision Tree, Artificial Neural Networks, Logistic Regression, Bankruptcy.

JEL Classification Codes

, C45, C53, G33

Paper Submission Date

, October 15, 2023, Paper sent back for Revision, February 10, 2024, Paper Acceptance Date, February 20, Paper Published Online, March 15, 2024

Abstract

Purpose : The primary goal was to forecast insolvency by comparing different bankruptcy prediction methods among Indian industrial enterprises.

Methodology : This study assessed the use of machine learning models in the financial industry. A comparison of random forests (RFs), decision trees (DTs), artificial neural networks (ANNs), and logistic regression was done. The consideration period for companies that were declared bankrupt under the 2016 Insolvency and Bankruptcy Code was April 1, 2017, until March 31, 2020. Data from 48 companies, 24 of which were bankrupt and 24 of which were not, was gathered two years ago.

Findings : In the comparative examination, the RF predictive technique outperformed the other predictive strategies in terms of accuracy.

Practical Implications : A company’s financial characteristics provide valuable insights into its overall financial well-being. Examining a field of information that would be fascinating to regulators and investors will be facilitated by this study.

Originality : There has been little research on bankrupt companies after the IBC 2016 took effect. This study concentrated on predicting a company’s bankruptcy following the implementation of the 2016 Insolvency and Bankruptcy Code.

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Published

2024-03-01

How to Cite

Kaur, S., Arora, A., Goyal, A. K., & Munde, A. (2024). Bankruptcy Prediction of Manufacturing Companies of India Post-IBC : A Comparative Study Between Various Predictive Techniques. Indian Journal of Finance, 18(3), 25–42. https://doi.org/10.17010/ijf/2024/v18i3/173615

Issue

Volume 18, Issue 3, March 2024

Section

Articles
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