TY  - DATA
AU  - Deva, Aditya
AU  - Kumar, Karan
TI  - Bankruptcy prediction model using financials and non-financials variables by employing logistic regression
U1  - SP2023/3718 
PY  - 2023///
CY  - Ahmedabad
PB  - Indian Institute of Management
KW  - IBBI
KW  - Machine learning
KW  - Logistic regression
KW  - financial creditor (FC)
N1  - Submitted to Prof. Prashant Das

Submitted by: Aditya Deva, Karan Kumar
N2  - Bankruptcy prediction involves evaluating a company's creditworthiness and financial health to determine the likelihood of it going bankrupt in the future. Creditors use these predictions to make informed decisions about extending credit, adjusting credit terms, and formulating risk management strategies. Insolvency refers to a financial state in which an individual or entity is unable to meet its financial obligations or pay its debts when they come due. Bankruptcy is a legal process that provides a formal solution to address the issues of insolvency. It offers a structured framework for managing and resolving financial difficulties while protecting the rights of both debtors and creditors. The Insolvency and Bankruptcy Code (IBC) of India, enacted in 2016, has brought about a structured process for resolving insolvency cases. This has led to increased transparency around the duration, claims, and haircut (loss of claim amount) associated with insolvency. The IBC also enables a creditor-in-control process, where the insolvency initiation from the creditor/debtor leads to an outcome of liquidation or resolution of the defaulted company. The outcome of the insolvency process has a significant impact on the extent of credit forgone by the financial and operational creditors of the company
ER  -