Legal contracts are complex documents containing clauses that may introduce financial, legal, or compliance-related risks. Manual analysis of such contracts is time-consuming and prone to human error. This research presents an AI-based Legal Contract Risk Analyzer that utilizes Natural Language Processing (NLP), transformer-based architectures such as BERT and LegalBERT, and machine learning techniques to automatically analyze legal contracts and identify potentially risky clauses. The proposed system performs preprocessing, text extraction, semantic analysis, clause classification, and risk prediction to improve contract review efficiency. The model aims to assist legal professionals, organizations, and businesses in reducing legal risks and enhancing decision-making through intelligent contract analysis.
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Rajeshirke et al. (2026) studied this question.
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