ISEP – DEI – Comunicações em eventos científicos
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- Automated extraction of insurance product characteristicsPublication . Oliveira, Francisco; Sousa, Paulo Gandra de; Faria, Luiz; Faria, Luiz; Cardoso, Duarte; Teixeira, JoãoThe increasing complexity and diversity of insurance products have highlighted the need for efficient methods to interpret and manage the detailed information present in regulatory documents. This project explores the application of Natural Language Processing (NLP) and Large Language Models (LLMs) in the automatic extraction of relevant characteristics of these products, addressing challenges such as structuring technical texts and accurately identifying rules, conditions, and variations. The research focuses on analyzing the state of the art in technologies such as vector databases, LLMs, knowledge graphs, and agentic workflows, as well as evaluating NLP tools and methodologies. The text goes on to explore the primary challenges encountered during the interpretation of insurance documentation, as well as the transformation of unstructured data into organized formats that are compatible with modelling systems. The solution developed responded satisfactorily to the objectives established, enabling the structured and consistent extraction of product characteristics from regulatory documents. To this end, AI agent-based workflows were used, supported by LLMs and validation schemes, ensuring the quality and consistency of the results.