
Table of Contents
- I. Abstract
- II. The Problem of Institutional Data Scarcity
- III. Understanding Where the Data Lives
- IV. Automating What Humans Can’t Do
- V. Rebuilding Cases as Procedural Timelines
- VI.Capturing Resolution Documents from the IBBI
- VII. Why This Matters for Legal Research
- VIII. Policy implication
- IX. Conclusion
I. Abstract
India’s insolvency infrastructure generates a huge amount of information, but most of it sits scattered across government websites in formats that are difficult to analyse. This blog is set out to bridge that gap. By combining browser automation, HTML parsing, and automated document retrieval, it shows how raw tribunal records from the NCLT and IBBI can be transformed into a structured, research‑ready dataset. Instead of just capturing basic case information, the approach pieces together the entire procedural journey of insolvency cases, such as hearings, filings, interim applications, connected matters and turns them into meaningful data for empirical research.
II. The Problem of Institutional Data Scarcity
India’s Insolvency and Bankruptcy Code, 2016 was built on a single foundational premise: that creditor confidence depends on predictability. Investors must be able to look at Researchers studying India’s insolvency system run into a simple but stubborn problem: the institutions whose performance we want to measure are the same ones that hold the relevant data. The NCLT and the IBBI do publish their records publicly, but they are meant for interested parties to look up individual cases, not for statistical analysis. There’s no API, no bulk‑download option but just page‑by‑page searching.
The result is an odd mismatch: the information exists, but not in a form that anyone can easily analyse at scale. This study treats these websites as if they were databases in disguise and builds a method to extract the required information systematically.
The lack of structured datasets in the insolvency ecosystem has been noted by several researchers. Early empirical work by Chatterjee, Shaikh and Zaveri (2017) found that the information systems of the National Company Law Tribunal do not provide a complete lifecycle view of insolvency cases, with key variables such as filing dates, hearing dates and claim amounts often missing from published orders. Similar concerns regarding data fragmentation in judicial and quasi-judicial tribunals have been raised in earlier studies of India’s debt recovery framework (Ravi 2015; Regy & Roy 2017). More recent scholarship on insolvency reforms also emphasises that without systematic data publication, regulators and researchers cannot effectively evaluate institutional performance or policy outcomes (Mokal et al. 2022). These gaps force empirical researchers to construct datasets directly from administrative records through techniques such as automated web scraping and document extraction.
a distressed company and form a reasonable estimate of how much they will recover, and how long recovery will take. The National Company Law Tribunal (NCLT), operationalised on 1 June 2016, is the adjudicating authority through which that predictability is supposed to be delivered.
Evaluating whether the NCLT is delivering on that promise ought to be a straightforward empirical exercise. It is not. As DAKSH observed, both institutions “operate as black-boxes, and their functioning can be difficult to understand, not just for litigants, but even for the lawyers who argue before them.”


