Convergencia de inteligencia artificial y Blockchain para el fortalecimiento de la seguridad en plataformas FinTech
DOI:
https://doi.org/10.24215/15146774e096Palabras clave:
fintech, inteligencia artificial, blockchain, ciberseguridad financiera, regtech, prevención de fraudes, trazabilidadResumen
La convergencia entre inteligencia artificial (IA) y tecnología blockchain se ha consolidado como un eje central de la seguridad financiera en el ecosistema FinTech. Este trabajo se basa en un análisis sistemático de la literatura que examina el aporte de ambas tecnologías en áreas críticas como la detección de fraudes, la protección de datos sensibles, el cumplimiento regulatorio (KYC/AML), la trazabilidad y la gestión de riesgos. Los resultados muestran que la integración de IA y blockchain fortalece la resiliencia de las plataformas financieras y optimiza procesos regulatorios, aunque persisten desafíos de escalabilidad, interoperabilidad, sesgos algorítmicos y marcos regulatorios incompletos. El trabajo sintetiza el estado actual, las principales limitaciones y las oportunidades de estas tecnologías para mejorar la seguridad en Fin-Tech.
Referencias
Ahmadjee, S., Mera-Gómez, C., Bahsoon, R. y Kazman, R. (2022). A study on blockchain architecture design decisions and their security attacks and threats. ACM Transactions on Software Engineering and Methodology, 31(2), 36e. https://doi.org/10.1145/3502740
Alarab, I., Prakoonwit, S. y Nacer, M. I. (2020). Comparative analysis using supervised learning methods for anti-money laundering in bitcoin. Proceedings of the 2020 5th International Conference on Machine Learning Technologies, 11–17. https://doi.org/10.1145/3409073.3409078
AlBenJasim, S., Dargahi, T., Takruri, H. y Al-Zaidi, R. (2024). FinTech cybersecurity challenges and regulations: Bahrain case study. Journal of Computer Information Systems, 64(6), 835–851. https://doi.org/10.1080/08874417.2023.2251455
Becker, M., Merz, K. y Buchkremer, R. (2020). Regtech—the application of modern information technology in regulatory affairs: Areas of interest in research and practice [ISAFM-19-052.R1]. Intelligent Systems in Accounting, Finance and Management, 27(4), 161–167. https://doi.org/10.1002/isaf.1479
Chen, S. (2022). Cryptocurrency financial risk analysis based on deep machine learning. Complexity, 2022(1), 2611063. https://doi.org/10.1155/2022/2611063
Deng, R., Jiang, J., Ou, C., Chen, Z. y Li, H. (2024). Current status and prospects of risk management research in the era of big data intelligence. Proceedings of the 2023 3rd International Conference on Big Data, Artificial Intelligence and Risk Management, 859–864. https://doi.org/10.1145/3656766.3656908
Faccia, A., Moşteanu, N. R., Cavaliere, L. P. L. y Mataruna-Dos-Santos, L. J. (2020). Electronic money laundering, the dark side of fintech: An overview of the most recent cases. Proceedings of the 2020 12th International Conference on Information Management and Engineering, 29–34. https://doi.org/10.1145/3430279.3430284
Garanina, T., Ranta, M. y Dumay, J. (2021). Blockchain in accounting research: Current trends and emerging topics [Ahead of print]. Accounting, Auditing & Accountability Journal, 35(7), 1507–1533. https://doi.org/10.1108/AAAJ-10-2020-4991
Gunasinghe, H., Kundu, A., Bertino, E., Krawczyk, H., Chari, S., Singh, K. y Su, D. (2019). Prividex: Privacy preserving and secure exchange of digital identity assets. The World Wide Web Conference, 594–604. https://doi.org/10.1145/3308558.3313574
Habib Ullah Khan, M. Z. y Maliha. (2024). Identifying the ai-based solutions proposed for restricting money laundering in financial sectors: Systematic mapping. Applied Artificial Intelligence, 38(1), 1–18. https://doi.org/10.1080/08839514.2024.2344415
Huang, H., Pin-Hsuan Chang, B., Zhou-Peng Liao, C. y Chen, D.-Y. (2021). A matter of risk management: The effects of the innovation sandboxes on citizens’ risk perceptions. Proceedings of the 22nd Annual International Conference on Digital Government Research, 281–285. https://doi.org/10.1145/3463677.3463738
Ibarra, G. A. y Gindre, F. (2025). Inteligencia artificial y blockchain: Impactos en la mejora de la seguridad en plataformas fintech. JAIIO, Jornadas Argentinas de Informática, 11(7), 62–66.
Kaur, G. (2024). Privacy implications of central bank digital currencies (cbdcs): A systematic review of literature. EDPACS, 69(9), 87–123. https://doi.org/10.1080/07366981.2024.2376794
Lagerwaard, P. (2023). Financial surveillance and the role of the financial intelligence unit (fiu) in the netherlands. Journal of Money Laundering Control, 26(7), 63–84. https://doi.org/10.1108/JMLC-09-2022-0134
Li, B. y Xu, Z. (2022). A comprehensive bibliometric analysis of financial innovation. Economic Research-Ekonomska Istraživanja, 35(1), 367–390. https://doi.org/10.1080/1331677X.2021.1893203
Li, W., Paraschiv, F. y Sermpinis, G. (2022). A data-driven explainable case-based reasoning approach for financial risk detection. Quantitative Finance, 22(12), 2257–2274. https://doi.org/10.1080/14697688.2022.2118071
Liang, W., Liu, Y., Yang, C., Xie, S., Li, K. y Susilo, W. (2024). On identity, transaction, and smart contract privacy on permissioned and permissionless blockchain: A comprehensive survey. ACM Computing Surveys, 56(12), 298. https://doi.org/10.1145/3676164
Liu, J., Xu, Z., Li, R., Zhao, H., Jiang, H., Yao, J., Yuan, D. y Chen, S. (2021). Applying blockchain for primary financial market: A survey. IET Blockchain, 1(2–4), 65–81. https://doi.org/10.1049/blc2.12009
Lohachab, A., Garg, S., Kang, B., Amin, M. B., Lee, J., Chen, S. y Xu, X. (2021). Towards interconnected blockchains: A comprehensive review of the role of interoperability among disparate blockchains. ACM Computing Surveys, 54(7), 135. https://doi.org/10.1145/3460287
McCarthy, J. (2023). The regulation of regtech and suptech in finance: Ensuring consistency in principle and in practice. Journal of Financial Regulation and Compliance, 31(2), 186–199. https://doi.org/10.1108/JFRC-01-2022-0004
Nicholls, J., Kuppa, A. y Le-Khac, N.-A. (2023). Fraudlens: Graph structural learning for bitcoin illicit activity identification. ACSAC '23: Proceedings of the 39th Annual Computer Security Applications Conference, 324–336. https://doi.org/10.1145/3627106.3627200
Nofie, I. (2020). The rise and rise of financial technology: The good, the bad, and the verdict. Cogent Business & Management, 7(1), 1725309. https://doi.org/10.1080/23311975.2020.1725309
Nokhbeh Zaeem, R., Chang, K. C., Huang, T.-C., Liau, D., Song, W., Tyagi, A., Khalil, M., Lamison, M., Pandey, S. y Barber, K. S. (2022). Blockchain based self-sovereign identity: Survey, requirements, use-cases, and comparative study. WI-IAT '21: IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, 128–135. https://doi.org/10.1145/3486622.3493917
Oude Roelink, B., El-Hajj, M. y Sarmah, D. (2024). Systematic review: Comparing zk-snark, zk-stark, and bulletproof protocols for privacy-preserving authentication. Security and Privacy, 7(5), e401. https://doi.org/10.1002/spy2.401
Paterson, J. M. (2021). Making robo-advisers careful? duties of care in providing automated financial advice to consumers. Law and Financial Markets Review, 15(3-4), 278–295. https://doi.org/10.1080/17521440.2023.2196027
Qi, Y. y Xiao, J. (2018). Fintech: Ai powers financial services to improve people’s lives. Communications of the ACM, 61(11), 65–69. https://doi.org/10.1145/3239550
Qudah, H., Baqila, B. K. A., Albadienah, J. M. O., AlQudah, M. Z., Al Qudah, S., Alrahamneh, S., Ababneh, A. y Qudah, I. (2024). Using bibliometrics to understand algorithmic finance. Journal of Applied Economics, 27(1), 2389497. https://doi.org/10.1080/15140326.2024.2389497
Vedapradha, R. y Hariharan, R. (2021). Innovation in banking: Fusion of artificial intelligence and blockchain. Asia Pacific Journal of Innovation and Entrepreneurship, 15(1), 51–61. https://doi.org/10.1108/APJIE-09-2020-0142
Ren, Y., Ren, Y., Tian, H., Song, W. y Yang, Y. (2023). Improving transaction safety via anti-fraud protection based on blockchain. Connection Science, 35(1), 2163983. https://doi.org/10.1080/09540091.2022.2163983
Samonte, M. J. C. y Navarro, A. L. E. S. (2024). Unleashing the power of ai: Seeking the impact of artificial intelligence in the fintech industry. Proceedings of the 2024 6th International Conference on Management Science and Industrial Engineering, 196–201. https://doi.org/10.1145/3664968.3664993
Samonte, M. J. C., Villasor, D. A. E., Sudo, K. F. M. y Layno, R. S. (2024). Analyzing artificial intelligence as business strategy in fighting fraud in the fintech industry. ICCAI '24: Proceedings of the 2024 10th International Conference on Computing and Artificial Intellige, 319–324. https://doi.org/10.1145/3669754.3669803
Soltani, R., Nguyen, U. T. y An, A. (2021). A survey of self-sovereign identity ecosystem. Security and Communication Networks, 2021(1), 8873429. https://doi.org/10.1155/2021/8873429
Truby, J., Brown, R. y Dahdal, A. (2020). Banking on ai: Mandating a proactive approach to ai regulation in the financial sector. Law and Financial Markets Review, 14(2), 110–120. https://doi.org/10.1080/17521440. 2020.1760454
van Wegberg, R., Oerlemans, J.-J. y van Deventer, O. (2018). Bitcoin money laundering: Mixed results? Journal of Financial Crime, 25(2), 419–435. https://doi.org/10.1108/JFC-11-2016-0067
Wen, Y. (2024). Research on risk early warning system of financial sharing platform based on neural network model. DEAI '24: Proceedings of the 2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence, 943–947. https://doi.org/10.1145/3675417.3675573
Wong, M. C. S., Chan, E. K. H. y Yousaf, I. (2024). Cbdcs, regulated stablecoins, and tokenized traditional assets under the basel committee rules on cryptoassets. Journal of Financial Regulation and Compliance, 33(1), 31–47. https://doi.org/10.1108/JFRC-03-2024-0050
Wu, H., Yao, Q., Liu, Z., Huang, B., Zhuang, Y., Tang, H. y Liu, E. (2024). Blockchain for finance: A survey. IET Blockchain, 4(2), 101–123. https://doi.org/10.1049/blc2.12067
Zakaria, N., Sulaiman, A., Min, F. S. y Feizollah, A. (2023). Machine learning in the financial industry: A bibliometric approach to evidencing applications. Cogent Social Sciences, 9(2), 2276609. https://doi.org/10.1080/23311886.2023.2276609
Zhang, R., Xue, R. y Liu, L. (2019). Security and privacy on blockchain. ACM Computing Surveys, 52(3), 51. https://doi.org/10.1145/3316481
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Derechos de autor 2026 Gabriel A. Ibarra, Francisco Gindre
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