Using textual analysis in bankruptcy prediction: Evidence from Indian firms under IBC

Abstract

Identifying and managing credit risk is vital for all lending institutions. Historically, credit risk is assessed using financial data from published financial statements. However, research indicates that the ability to detect financial hardship may be improved by textual analysis of firms’ disclosed records. This study aims to establish an association between themes and words from Management Discussion and Analysis (MDA) reports of firms and corporate failures. The study took a sample of 57 Indian listed firms declared bankrupt under the Insolvency and Bankruptcy Code (IBC) along with a matched sample of 55 solvent firms (matched by industry and size) for the period of FY2011–2019. The first part of analysis identifies negative words from the published reports and compares them with the negative words of the Loughran-McDonald dictionary. Then a thematic analysis is done to identify the key themes from the MDA reports and the significant themes are validated with their corresponding financial ratios in the third step using a panel logistic regression. Word analysis results show that IBC firms have significantly greater negative tone (2.21 percent) as against 1.30 percent of solvent firms. Thematic analysis results show that manageability, activity and performance are significant themes for predicting financial distress. Financial variables such as ownership pattern, promoters’ shares pledged, return on capital employed, asset utilization are some of the ratios in sync with the key themes. The study recommends that lenders and other stakeholders should look beyond financial statements which may be ‘window dressed’ by firms to qualitative disclosures in annual reports which may forewarn against impending financial distress. Acknowledgments The infrastructural support provided by FORE School of Management, New Delhi in completing this paper is gratefully acknowledged.