Bankruptcy Prediction using Multivariate Discriminant Analysis – Empirical Evidence from Cases Referred to NCLT
Rajalakshmi Vel1, Priyanka Zala2

1Dr. Rajalakshmi Vel, School of Management, Vel Tech Rangarajan Dr.Sagunthala R & D Institute of Science and Technology, Chennai, India.
2Dr. Priyanka Zala, Faculty of Business Administration, GLS University, Ahmedabad, India.
Manuscript received on 30 June 2019 | Revised Manuscript received on 05 July 2019 | Manuscript published on 30 July 2019 | PP: 13-17 | Volume-8 Issue-9, July 2019 | Retrieval Number: I7496078919/19©BEIESP | DOI: 10.35940/ijitee.I7496.078919
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Abstract: The study is about bankruptcy prediction using multivariate model of analysis for the case of twelve large accounts which were referred to National Company Law Tribunal for insolvency proceedings. Corporate failures affect all stakeholders. It’s also a fact that companies are never shielded from bankruptcy. With the mounting of India’s non-performing assets, the pronouncement of Insolvency and Bankruptcy Code is a strong suit for maximising value of lenders as well as borrowers. The first part of the paper throws light on the code, the progress made and challenges faced. On the empirical literature side, the paper applies the famous Altman’s Z-Score model on the first twelve companies on which insolvency proceedings are on. Suitability of the model is supported by literature review on the subject. Financial data gathered from Annual reports are analysed to arrive at Z-Score results. The strength of the results are statistically examined through hypotheses tested using regression and feasibility of the model is tested using ANOVA. The paper presents the limitation of the study, a discussion of the suitability of the model and further scope of research in the area.
Keywords: Altman’s Z-Score, Bankruptcy prediction, Financial ratios, Insolvency and Bankruptcy Code (IBC), National Company Law Tribunal (NCLT)

Scope of the Article:  Regression and Prediction