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Automated extraction of insurance product characteristics

datacite.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
dc.contributor.authorOliveira, Francisco
dc.contributor.authorSousa, Paulo Gandra de
dc.contributor.authorFaria, Luiz
dc.contributor.authorFaria, Luiz
dc.contributor.authorCardoso, Duarte
dc.contributor.authorTeixeira, João
dc.date.accessioned2026-04-23T07:25:41Z
dc.date.available2026-04-23T07:25:41Z
dc.date.issued2025-12-09
dc.description.abstractThe 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.eng
dc.identifier.citationTeixeira, J., Sousa, P. G., Faria, L., Cardoso, D. & Oliveira, F. (2025, dezembro 9). Simplifying complex insurance product management with AI. In Sá, C., Oliveira, C., Silva, E., Cardoso, M., Morgado, N., Proença, P., Carvalho, P., Vieira, R., Meireles, R., & Moreira, S. (Eds.). Simpósio de Engenharia Informática 2025. Instituto Superior de Engenharia do Porto ISEP – P.Porto
dc.identifier.isbn978-989-36167-7-2
dc.identifier.urihttp://hdl.handle.net/10400.22/32275
dc.language.isoeng
dc.peerreviewedyes
dc.publisherInstituto Superior de Engenharia do Porto (ISEP) – P.Porto
dc.relation.hasversionhttps://sei.dei.isep.ipp.pt/
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectDocument extraction
dc.subjectNamed Entity Recognition
dc.subjectLarge Language Models
dc.subjectAI Agentic Workflows
dc.subjectInsurance Product
dc.titleAutomated extraction of insurance product characteristicseng
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferenceDate2025-12-09
oaire.citation.conferencePlacePorto, Portugal
oaire.citation.titleSEI'25 - Simpósio de Engenharia Informática 2025
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameFaria
person.givenNameLuiz
person.identifier.orcid0000-0002-1169-7785
person.identifier.scopus-author-id7005022382
relation.isAuthorOfPublication9de0e99c-714f-4ccd-9d43-0740f2ed662c
relation.isAuthorOfPublication.latestForDiscovery9de0e99c-714f-4ccd-9d43-0740f2ed662c

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