Design and Implementation of an Automated CFDI Analysis Algorithm for Accounting and Tax Optimization in SMEs
DOI:
https://doi.org/10.61467/2007.1558.2026.v17i1.1214Keywords:
Digital Tax Receipts, process productivity, robotic accounting, sequential algorithmAbstract
This study aimed to develop and evaluate an algorithm designed to reduce the time required for the analysis of Digital Tax Receipts (CFDI), with application to small and medium-sized enterprises (SMEs). Using a mixed and experimental approach, the performance of the algorithm was compared with manual review conducted by 170 Financial Engineering students. The results indicated that the algorithm was significantly more efficient, achieving an average reduction of 220.14 seconds and a very large effect size (Cohen’s d = 3.77). Furthermore, the algorithm achieved an effectiveness rate of 88% in determining the validity of CFDIs with respect to their deductibility for tax purposes, thereby highlighting its potential to optimise processes, improve productivity, and support decision-making in accounting and organisational contexts.
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References
Abdullah, A. A. H., & Almaqtari, F. A. (2024). The impact of artificial intelligence and Industry 4.0 on transforming accounting and auditing practices. Journal of Open Innovation: Technology, Market, and Complexity, 10(1), Article 100218. https://doi.org/10.1016/j.joitmc.2024.100218
Burga Jadán, M. F. (2023). La gestión financiera en las pequeñas y medianas empresas. Revista Yura, (34), 55–72. https://yura.espe.edu.ec/wp-content/uploads/2023/06/34.4-La-gestion-financiera-en-las-Pequenas-y-Medianas-Empresas.pdf
Cheng, X., Dunn, R., Holt, T., Inger, K., Jenkins, G., Jones, J., & Wood, D. (2024). Artificial intelligence’s capabilities, limitations, and impact on accounting education: Investigating ChatGPT’s performance on educational accounting cases. Issues in Accounting Education, 39(2), 23–47. https://doi.org/10.2308/ISSUES-2023-032
Fülöp, M., Topor, D., Ionescu, C., Capusneanu, S., Breaz, T., and Stanescu, S. (2022). Fintech accounting and Industry 4.0: Future-proofing or threats to the accounting profession? Journal of Business Economics and Management, 23(5), 997-1015. https://doi.org/10.3846/jbem.2022.17695
García-Vera, Y. S., Juca-Maldonado, F. X., & Torres-Gallegos, V. (2023). Automatización de procesos contables mediante inteligencia artificial: Oportunidades y desafíos para pequeños empresarios ecuatorianos. Revista Transdisciplinaria de Estudios Sociales y Tecnológicos, 3(3), 68–74. https://doi.org/10.58594/rtest.v3i3.93
Handoyo, S. (2024). Evolving paradigms in accounting education: A bibliometric study on the impact of information technology. International Journal of Management Education, 22(3), 1-21. https://doi.org/10.1016/j.ijme.2024.100998
Instituto Nacional de Estadística y Geografía. (2015). Tribunales de lo contencioso administrativo, 2013 (Documentos de análisis y estadísticas). https://www.inegi.org.mx/contenidos/productos/prod_serv/contenidos/espanol/bvinegi/productos/nueva_estruc/702825078089.pdf
Larios, O., and Atoche, C. (2023). La automatización robótica de procesos y su relación con la operatividad de los procesos contables en las empresas de telecomunicaciones y banca en los países de Argentina, Chile, Colombia y Perú en el año 2021. Contabilidad y Negocios, 18(35), 67-95. https://doi.org/10.18800/contabilidad.202301.001
Moll, J., & Yigitbasioglu, O. (2019). The role of information technology in shaping the future of accounting. The British Accounting Review, 51(6), Article 100833. https://doi.org/10.1016/j.bar.2019.04.002
Montagnani, M. L., Najjar, M.-C., & Davola, A. (2024). The EU regulatory approach(es) to AI liability, and its application to the financial services market. Computer Law & Security Review, 53, 105984. https://doi.org/10.1016/j.clsr.2024.105984
Montero Cortés, L. J. (2022). Análisis de la ganancia de aprendizaje en la enseñanza de las ecuaciones lineales implementando un entorno personal de aprendizaje. CITAS, 8(1), 1–15. https://doi.org/10.15332/24224529.7560
Özcan, E. Ç., & Akkaya, B. (2020). The effect of Industry 4.0 on accounting in terms of business management (Chapter 8). En B. Akkaya (Ed.), Agile business leadership methods for Industry 4.0 (pp. 139-154). Emerald Publishing Limited. https://doi.org/10.1108/978-1-80043-380-920201009
Pallathadka, H., Ramirez, E., Loli, T., Kaliyaperumal, K., Magno, R., and Naved, M. (2023). Applications of artificial intelligence in business management, e-commerce and finance. Materials Today: Proceedings, 80 (Part 3), 2610-2613. https://doi.org/10.1016/j.matpr.2021.06.419
Perifanis, N.-A., & Kitsios, F. (2023). Investigating the influence of artificial intelligence on business value in the digital era of strategy: A literature review. Information, 14(2), 85. https://doi.org/10.3390/info14020085
Rizzo-Mena, D. D., & Plaza, C. (2024). Un modelo de gestión específico para PYMES que mejora la productividad de los procesos mediante la implementación de herramientas imprescindibles de calidad. Journal Scientific Investigar, 8(1), 519–534. https://doi.org/10.56048/MQR20225.8.1.2024.519-534
Vărzaru, A. A. (2022). Assessing artificial intelligence technology acceptance in managerial accounting. Electronics, 11(14), 2256. https://doi.org/10.3390/electronics11142256
Wassie, F. A., & Lakatos, L. P. (2024). Artificial intelligence and the future of the internal audit function. Humanities and Social Sciences Communications, 11, Article 386. https://doi.org/10.1057/s41599-024-02905-w
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