Inteligencia artificial en la automatización de procesos contables análisis de las revistas, autores y tendencias más relevantes
La automatización de los procesos contables ha sido un objetivo clave para divulgar y promocionar la eficiencia y la rapidez de la gestión financiera en empresas que utilicen modelos de inteligencia artificial, a través de herramientas como el procesamiento y aprendizaje automático del lenguaje natu...
- Autores:
-
Morales Silva, Rafael Omar
Barrera Villalba, Liz Daniela
Doria Urango, Vibian Margarita
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2024
- Institución:
- Universidad Cooperativa de Colombia
- Repositorio:
- Repositorio UCC
- Idioma:
- spa
- OAI Identifier:
- oai:repository.ucc.edu.co:20.500.12494/55775
- Acceso en línea:
- https://hdl.handle.net/20.500.12494/55775
- Palabra clave:
- Inteligencia artificial
Automatización de procesos
Optimización
Artificial intelligence
Process automation
Optimization
- Rights
- closedAccess
- License
- http://creativecommons.org/publicdomain/zero/1.0/
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dc.title.spa.fl_str_mv |
Inteligencia artificial en la automatización de procesos contables análisis de las revistas, autores y tendencias más relevantes |
title |
Inteligencia artificial en la automatización de procesos contables análisis de las revistas, autores y tendencias más relevantes |
spellingShingle |
Inteligencia artificial en la automatización de procesos contables análisis de las revistas, autores y tendencias más relevantes Inteligencia artificial Automatización de procesos Optimización Artificial intelligence Process automation Optimization |
title_short |
Inteligencia artificial en la automatización de procesos contables análisis de las revistas, autores y tendencias más relevantes |
title_full |
Inteligencia artificial en la automatización de procesos contables análisis de las revistas, autores y tendencias más relevantes |
title_fullStr |
Inteligencia artificial en la automatización de procesos contables análisis de las revistas, autores y tendencias más relevantes |
title_full_unstemmed |
Inteligencia artificial en la automatización de procesos contables análisis de las revistas, autores y tendencias más relevantes |
title_sort |
Inteligencia artificial en la automatización de procesos contables análisis de las revistas, autores y tendencias más relevantes |
dc.creator.fl_str_mv |
Morales Silva, Rafael Omar Barrera Villalba, Liz Daniela Doria Urango, Vibian Margarita |
dc.contributor.advisor.none.fl_str_mv |
Llanos Ayola, Jones Rafael |
dc.contributor.author.none.fl_str_mv |
Morales Silva, Rafael Omar Barrera Villalba, Liz Daniela Doria Urango, Vibian Margarita |
dc.contributor.corporatename.none.fl_str_mv |
Universidad Cooperativa de Colombia |
dc.subject.proposal.spa.fl_str_mv |
Inteligencia artificial Automatización de procesos Optimización |
topic |
Inteligencia artificial Automatización de procesos Optimización Artificial intelligence Process automation Optimization |
dc.subject.proposal.eng.fl_str_mv |
Artificial intelligence Process automation Optimization |
description |
La automatización de los procesos contables ha sido un objetivo clave para divulgar y promocionar la eficiencia y la rapidez de la gestión financiera en empresas que utilicen modelos de inteligencia artificial, a través de herramientas como el procesamiento y aprendizaje automático del lenguaje natural, ha permitido desarrollar sistemas capaces de realizar tareas contables complejas de manera autónoma. Esto incluye desde el análisis de las transacciones hasta la clasificación de informes financieros, reduciendo la carga de trabajo manual y aumentando la capacidad de análisis predictivo. En el presente trabajo, se plantearon objetivos específicos que incluyeron la revisión de la literatura existente sobre el comportamiento de la inteligencia artificial en los procesos contables y la documentación de la automatización de estos procesos mediante el uso de inteligencia artificial. La metodología empleada fue de tipo cuantitativo y descriptivo, utilizando técnicas bibliométricas para seleccionar una muestra representativa de 169 investigaciones publicadas desde 1972 hasta la actualidad. Se aplicaron criterios de selección rigurosos para garantizar la validez y la coherencia de los resultados obtenidos. Finalmente, los resultados concluyeron un creciente interés y evolución en el uso de inteligencia artificial en los procesos contables, evidenciando su potencial transformador para optimizar recursos, mejorar la calidad de la información y reducir errores humanos. Se identificaron aplicaciones de la inteligencia artificial, desde la automatización de tareas hasta la generación de análisis avanzados, subrayando a importancia en la operatividad y competitividad de la organización. |
publishDate |
2024 |
dc.date.accessioned.none.fl_str_mv |
2024-06-04T17:39:19Z |
dc.date.available.none.fl_str_mv |
2024-06-04T17:39:19Z 2026-06-30 |
dc.date.issued.none.fl_str_mv |
2024-06-04 |
dc.type.none.fl_str_mv |
Trabajo de grado - Pregrado |
dc.type.coar.none.fl_str_mv |
http://purl.org/coar/resource_type/c_7a1f |
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info:eu-repo/semantics/bachelorThesis |
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info:eu-repo/semantics/acceptedVersion |
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http://purl.org/coar/resource_type/c_7a1f |
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acceptedVersion |
dc.identifier.citation.none.fl_str_mv |
Morales Silva, R. O., Barrera Villalba, L. D. y Doria Urango, V. M. (2024). Inteligencia artificial en la automatización de procesos contables análisis de las revistas, autores y tendencias más relevantes [Tesis de pregrado, Universidad Cooperativa de Colombia] Repositorio Institucional Universidad Cooperativa de Colombia. https://hdl.handle.net/20.500.12494/55775 |
dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12494/55775 |
identifier_str_mv |
Morales Silva, R. O., Barrera Villalba, L. D. y Doria Urango, V. M. (2024). Inteligencia artificial en la automatización de procesos contables análisis de las revistas, autores y tendencias más relevantes [Tesis de pregrado, Universidad Cooperativa de Colombia] Repositorio Institucional Universidad Cooperativa de Colombia. https://hdl.handle.net/20.500.12494/55775 |
url |
https://hdl.handle.net/20.500.12494/55775 |
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language |
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(2022). Is artificial intelligence improving the audit process? Review of Accounting Studies. Scopus. https://doi.org/10.1007/s11142-022-09697-x Galaz, V., Centeno, M. A., Callahan, P. W., Causevic, A., Patterson, T., Brass, I., Baum, S., Farber, D., Fischer, J., Garcia, D., McPhearson, T., Jimenez, D., King, B., Larcey, P., & Levy, K. (2021). Artificial intelligence, systemic risks, and sustainability. Technology in Society, 67, 101741. https://doi.org/10.1016/j.techsoc.2021.101741 Gaviria, D. A. G., Polo, O. C. C., Martínez, E. M. C., & García-Arango, D. A. (2022). Influence of the Fourth Industrial Revolution on the Ethics of the Colombian Accounting Professional. Procedia Computer Science, 215, 626-641. https://doi.org/10.1016/j.procs.2022.12.065 Gómez-Ríos, D., Ramírez-Malule, H., & Marriaga-Cabrales, N. (2023). Mesocurriculum modernization of a chemical engineering program: The case of a high-impact regional university in Colombia. 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The Importance of Strategic Thinking and Innovation for the Growth of SMEs: Case of the Colombian SMEs. Procedia Computer Science, 224, 495-501. https://doi.org/10.1016/j.procs.2023.09.071 Hong, Z., & Xiao, K. (2024). Digital economy structuring for sustainable development: The role of blockchain and artificial intelligence in improving supply chain and reducing negative environmental impacts. Scientific Reports, 14(1). Scopus. https://doi.org/10.1038/s41598-024-53760-3 Igou, A., Power, D. J., Brosnan, S., & Heavin, C. (2023). Digital futures for accountants. Journal of Emerging Technologies in Accounting, 20(1), 39-57. Scopus. https://doi.org/10.2308/JETA-2020-088 Ihsanullah, I., Alam, G., Jamal, A., & Shaik, F. (2022). Recent advances in applications of artificial intelligence in solid waste management: A review. Chemosphere, 309, 136631. https://doi.org/10.1016/j.chemosphere.2022.136631 Jackson, D., & Allen, C. (2024). Enablers, barriers and strategies for adopting new technology in accounting. International Journal of Accounting Information Systems, 52. Scopus. https://doi.org/10.1016/j.accinf.2023.100666 Kayser, K., & Telukdarie, A. (2024). Literature Review: Artificial Intelligence Adoption Within the Accounting Profession Applying the Technology Acceptance Model (3) (Moloi T. & George B., Eds.; pp. 217-231). Springer Nature; Scopus. https://doi.org/10.1007/978-3-031-46177-4_12 Korol, V., Dmytryk, O., Karpenko, O., Riadinska, V., Basiuk, O., Kobylnik, D., Moroz, V., Safronova, O., Alisov, E., & Mishchenko, T. (2022). ELABORATION OF RECOMMENDATIONS ON THE DEVELOPMENT OF THE STATE INTERNAL AUDIT SYSTEM WHEN APPLYING THE DIGITAL TECHNOLOGIES. Eastern-European Journal of Enterprise Technologies, 1(13-115), 39-48. Scopus. https://doi.org/10.15587/1729-4061.2022.252424 Lehner, O. M., Ittonen, K., Silvola, H., Ström, E., & Wührleitner, A. (2022). Artificial intelligence based decision-making in accounting and auditing: Ethical challenges and normative thinking. Accounting, Auditing and Accountability Journal, 35(9), 109-135. Scopus. https://doi.org/10.1108/AAAJ-09-2020-4934 Maestre-Góngora, G., & Aponte, D. (2023). Dataset about information technology governance: A survey in Colombian enterprises. Data in Brief, 50, 109480. https://doi.org/10.1016/j.dib.2023.109480 Meza, J. K. S., Yepes, D. O., Rodrigo-Ilarri, J., & Cassiraga, E. (2019). Predictive analysis of urban waste generation for the city of Bogotá, Colombia, through the implementation of decision trees-based machine learning, support vector machines and artificial neural networks. Heliyon, 5(11), e02810. https://doi.org/10.1016/j.heliyon.2019.e02810 Montalvo-Navarrete, J. M., & Lasso-Palacios, A. P. (2024). Energy access sustainability criteria definition for Colombian rural areas. Renewable and Sustainable Energy Reviews, 189, 113922. https://doi.org/10.1016/j.rser.2023.113922 Moreno, J. M., Sánchez, J. M., & Espitia, H. E. (2020). Use of computational intelligence techniques to predict flooding in places adjacent to the Magdalena River. Heliyon, 6(9), e04872. https://doi.org/10.1016/j.heliyon.2020.e04872 Nascimento, N. (2021). Wealth tax in brazil: Proposals and simulations. Revista de Economia Contemporanea, 25(3). Scopus. https://doi.org/10.1590/198055272533 Naught, C. (2023). Teaching advanced data analytics, robotic process automation, and artificial intelligence in a graduate accounting program. Journal of Emerging Technologies in Accounting, 20(1), 223-243. Scopus. https://doi.org/10.2308/JETA-2022-025 Nguyen, Q. H. (2023). Revisiting Uzawa–Lucas with public human capital spending and productivity heterogeneity. Studies in Economics and Finance, 40(2), 373-391. Scopus. https://doi.org/10.1108/SEF-03-2022-0149 Nguyen, Q. P., & Vo, D. H. (2022). 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Regional Science Policy & Practice, 100013. https://doi.org/10.1016/j.rspp.2024.100013 Peretz-Andersson, E., Tabares, S., Mikalef, P., & Parida, V. (2024). Artificial intelligence implementation in manufacturing SMEs: A resource orchestration approach. International Journal of Information Management, 77, 102781. https://doi.org/10.1016/j.ijinfomgt.2024.102781 Rad, M., Abtahi, A., Berndtsson, R., McKnight, U. S., & Aminifar, A. (2024). Interpretable machine learning for predicting the fate and transport of pentachlorophenol in groundwater. Environmental Pollution, 345. Scopus. https://doi.org/10.1016/j.envpol.2024.123449 Rahman, M. J., & Zhu, H. (2024). Detecting accounting fraud in family firms: Evidence from machine learning approaches. Advances in Accounting, 64. Scopus. https://doi.org/10.1016/j.adiac.2023.100722 Ramirez-Bautista, J. A., Chaparro-Cárdenas, S. L., Esmer, C., & Huerta-Ruelas, J. A. (2024). Artificial intelligence approaches to physiological parameter analysis in the monitoring and treatment of non-communicable diseases: A review. Biomedical Signal Processing and Control, 87, 105463. https://doi.org/10.1016/j.bspc.2023.105463 Rodgers, W., Murray, J. M., Stefanidis, A., Degbey, W. Y., & Tarba, S. Y. (2023). An artificial intelligence algorithmic approach to ethical decision-making in human resource management processes. Human Resource Management Review, 33(1). Scopus. https://doi.org/10.1016/j.hrmr.2022.100925 Sánchez, J. M., Rodríguez, J. P., & Espitia, H. E. (2022). Bibliometric analysis of publications discussing the use of the artificial intelligence technique agent-based models in sustainable agriculture. Heliyon, 8(12), e12005. https://doi.org/10.1016/j.heliyon.2022.e12005 Sattari, F., Lefsrud, L., Kurian, D., & Macciotta, R. (2022). A theoretical framework for data-driven artificial intelligence decision making for enhancing the asset integrity management system in the oil & gas sector. Journal of Loss Prevention in the Process Industries, 74, 104648. https://doi.org/10.1016/j.jlp.2021.104648 Thottoli, M. M. (2024). Leveraging information communication technology (ICT) and artificial intelligence (AI) to enhance auditing practices. Accounting Research Journal. Scopus. https://doi.org/10.1108/ARJ-09-2023-0269 Tiitola, V., Jalonen, T., Rantanen-Flores, M., Korhonen, T., Ruusuvuori, J., & Laine, T. (2024). Discourse analysis on sustaining the maieutic role “when management accounting goes digital”. Qualitative Research in Accounting and Management, 21(2), 140-164. Scopus. https://doi.org/10.1108/QRAM-11-2022-0198 Yang, F., Zou, C., & Li, C. (2023). The Impact of Carbon Tariffs on China’s Agricultural Trade. Agriculture (Switzerland), 13(5). Scopus. https://doi.org/10.3390/agriculture13051013 Zhen, X., & Zhen, L. (2024). Accounting Information Systems and Strategic Performance: The Interplay of Digital Technology and Edge Computing Devices. Journal of Grid Computing, 22(1). Scopus. https://doi.org/10.1007/s10723-023-09720-8 |
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Llanos Ayola, Jones RafaelMorales Silva, Rafael OmarBarrera Villalba, Liz DanielaDoria Urango, Vibian MargaritaUniversidad Cooperativa de Colombia2024-06-04T17:39:19Z2026-06-302024-06-04T17:39:19Z2024-06-04Morales Silva, R. O., Barrera Villalba, L. D. y Doria Urango, V. M. (2024). Inteligencia artificial en la automatización de procesos contables análisis de las revistas, autores y tendencias más relevantes [Tesis de pregrado, Universidad Cooperativa de Colombia] Repositorio Institucional Universidad Cooperativa de Colombia. https://hdl.handle.net/20.500.12494/55775https://hdl.handle.net/20.500.12494/55775La automatización de los procesos contables ha sido un objetivo clave para divulgar y promocionar la eficiencia y la rapidez de la gestión financiera en empresas que utilicen modelos de inteligencia artificial, a través de herramientas como el procesamiento y aprendizaje automático del lenguaje natural, ha permitido desarrollar sistemas capaces de realizar tareas contables complejas de manera autónoma. Esto incluye desde el análisis de las transacciones hasta la clasificación de informes financieros, reduciendo la carga de trabajo manual y aumentando la capacidad de análisis predictivo. En el presente trabajo, se plantearon objetivos específicos que incluyeron la revisión de la literatura existente sobre el comportamiento de la inteligencia artificial en los procesos contables y la documentación de la automatización de estos procesos mediante el uso de inteligencia artificial. La metodología empleada fue de tipo cuantitativo y descriptivo, utilizando técnicas bibliométricas para seleccionar una muestra representativa de 169 investigaciones publicadas desde 1972 hasta la actualidad. Se aplicaron criterios de selección rigurosos para garantizar la validez y la coherencia de los resultados obtenidos. Finalmente, los resultados concluyeron un creciente interés y evolución en el uso de inteligencia artificial en los procesos contables, evidenciando su potencial transformador para optimizar recursos, mejorar la calidad de la información y reducir errores humanos. Se identificaron aplicaciones de la inteligencia artificial, desde la automatización de tareas hasta la generación de análisis avanzados, subrayando a importancia en la operatividad y competitividad de la organización.The automation of accounting processes has been a key objective to improve the accuracy, efficiency and speed of financial management of organizations. Artificial intelligence, through tools such as natural language processing and machine learning, has made it possible to develop systems capable of performing complex accounting tasks autonomously. This includes everything from transaction analysis to financial report classification, reducing manual workload and increasing predictive analytics capabilities. In the present work, specific objectives were set that included the review of the existing literature on the behavior of artificial intelligence in accounting processes and the documentation of the automation of these processes through the use of artificial intelligence. The methodology used was quantitative and descriptive, using bibliometric techniques to select a representative sample of 169 studies published from 1972 to the present. Rigorous selection criteria were applied to ensure the validity and consistency of the results obtained. Finally, the results concluded a growing interest and evolution in the use of artificial intelligence in accounting processes, evidencing its transformative potential to optimize resources, improve the quality of information and reduce human errors. Applications of artificial intelligence were identified, from the automation of tasks to the generation of advanced analyses, underlining its importance in the operability and competitiveness of the organization.Resumen – Abstrac – Capítulo I. Problema -- 1.1 Objetivos -- 1.1.1 Objetivo general -- 1.1.2 -Objetivos específicos -- 1.2 Justificación -- Capítulo II. Antecedentes -- 2.1 Antecedentes – internacionales -- 2.2 Antecedentes nacionales -- 2.3 Marco Teórico -- Inteligencia artificial -- Tipos de inteligencia artificial -- Inteligencia artificial en procesos contables -- Automatización de procesos -- Capítulo III. Metodología -- 3.1 Tipo de investigación -- 3.2 Fuente de información -- 3.3 Técnica de búsqueda -- 3.4 Identificación y selección de resultados -- Capítulo IV. Resultados – 5. Conclusiones – 6. 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