Identification of unconventional patterns in double taxation agreements: an analysis based on AI-assisted natural language processing models
dc.contributor.advisor | Sánchez Fuentes, Antonio Jesús | |
dc.contributor.author | Díaz-Heredero López, Gonzalo | |
dc.date.accessioned | 2025-03-17T17:29:01Z | |
dc.date.available | 2025-03-17T17:29:01Z | |
dc.date.defense | 2025-01 | |
dc.date.issued | 2025-02 | |
dc.degree.title | Doble Grado en Derecho y ADE | |
dc.description.abstract | Este Trabajo de Fin de Grado analiza los Convenios de Doble Imposición firmados por España con siete países económicamente relevantes en términos de volumen de comercio e inversión, comparando cada tratado fiscal con el Convenio Modelo sobre la Renta y el Patrimonio de la Organización para la Cooperación y el Desarrollo Económico publicado en 2017, con el fin de identificar disposiciones no convencionales que revelen negociaciones bilaterales específicas entre España y el país extranjero. Este análisis se ha llevado a cabo mediante el uso de una Inteligencia Artificial especializada en Procesamiento de Lenguaje Natural, utilizando ingeniería del prompt y recuperación sencilla de archivos cargados al Modelo De Lenguaje Grande de última generación de Open AI llamado “GPT-4o". El fin del estudio es evaluar la capacidad del Modelo De Lenguaje Grande para mejorar la eficiencia y efectividad de los expertos fiscales internacionales al investigar tratados fiscales internacionales o documentos análogos, extrayendo y sintetizando información de manera sistemática y escalable. | |
dc.description.abstract | This Final Project Degree analyses Double Taxations Agreements signed by Spain with seven economically relevant countries in terms of trade volume and investment, comparing each tax treaty to the Organisation for Economic Co-operation and Development Model Tax Convention on Income and Capital published in 2017 with the purpose of identifying unconventional provisions that reveal specific bilateral negotiations between Spain and the foreign country. This analysis has been carried out through the use of an Artificial Intelligence specialized in Natural Language Processing, using prompt engineering and simple retrieval from uploaded files through OpenAI´s state of art Large Language Model called “GPT-4o”. The end of the study is to evaluate the Large Language Model´s capability to enhance international tax experts’ efficiency and effectiveness when investigating international tax treaties or analogue documents, extracting and synthesizing information in a systematic and scalable manner. | |
dc.description.department | Depto. de Economía Aplicada, Pública y Política | |
dc.description.faculty | Fac. de Ciencias Económicas y Empresariales | |
dc.description.refereed | TRUE | |
dc.description.status | pub | |
dc.identifier.uri | https://hdl.handle.net/20.500.14352/118839 | |
dc.language.iso | eng | |
dc.page.total | 121 | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | en |
dc.rights.accessRights | open access | |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.subject.keyword | OpenAI | |
dc.subject.keyword | Chat GPT | |
dc.subject.keyword | GPT-4o | |
dc.subject.keyword | Tax avoidance | |
dc.subject.keyword | International taxation | |
dc.subject.keyword | Prompt | |
dc.subject.keyword | Trade | |
dc.subject.keyword | Investment | |
dc.subject.ucm | Comercio | |
dc.subject.ucm | Inteligencia artificial (Informática) | |
dc.subject.unesco | 1203.04 Inteligencia Artificial | |
dc.subject.unesco | 5312.11 Comercio | |
dc.title | Identification of unconventional patterns in double taxation agreements: an analysis based on AI-assisted natural language processing models | |
dc.type | bachelor thesis | |
dc.type.hasVersion | AM | |
dspace.entity.type | Publication | |
relation.isAdvisorOfPublication | 2f0fcf85-e8d7-42d7-85b7-5a91da20d73b | |
relation.isAdvisorOfPublication.latestForDiscovery | 2f0fcf85-e8d7-42d7-85b7-5a91da20d73b |
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