Nyay-Darpan: Enhancing Decision Making Through Summarization and Case Retrieval for Consumer Law in India

TL;DR

Nyay-Darpan is a novel AI framework that summarizes consumer law cases and retrieves similar judgments to support decision-making in Indian consumer disputes, addressing a significant research gap.

Contribution

It introduces a combined summarization and case retrieval system specifically designed for Indian consumer law, with new evaluation methods and publicly available resources.

Findings

Achieves over 75% accuracy in similar case prediction

Attains approximately 70% accuracy in summary quality metrics

Provides a publicly available dataset and framework for further research

Abstract

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.