Nyay-Darpan: Enhancing Decision Making Through Summarization and Case Retrieval for Consumer Law in India
It addresses a gap in AI-based judicial assistance for consumer dispute resolution in India, which is an underexplored domain, though the approach appears incremental in applying existing techniques to this new area.
The paper tackles the lack of AI tools for consumer law in India by developing Nyay-Darpan, a framework that summarizes case files and retrieves similar judgements, achieving over 75% accuracy in case prediction and about 70% in summary evaluation metrics.
AI-based judicial assistance and case prediction have been extensively studied in criminal and civil domains, but remain largely unexplored in consumer law, especially in India. In this paper, we present Nyay-Darpan, a novel two-in-one framework that (i) summarizes consumer case files and (ii) retrieves similar case judgements to aid decision-making in consumer dispute resolution. Our methodology not only addresses the gap in consumer law AI tools but also introduces an innovative approach to evaluate the quality of the summary. The term 'Nyay-Darpan' translates into 'Mirror of Justice', symbolizing the ability of our tool to reflect the core of consumer disputes through precise summarization and intelligent case retrieval. Our system achieves over 75 percent accuracy in similar case prediction and approximately 70 percent accuracy across material summary evaluation metrics, demonstrating its practical effectiveness. We will publicly release the Nyay-Darpan framework and dataset to promote reproducibility and facilitate further research in this underexplored yet impactful domain.