Inteligencia Artificial en los servicios bancarios. Una revisión bibliométrica

Sergio Gerardo Padilla Hernández

doi:10.58763/rc2024335

Autores/as

Sergio Gerardo Padilla Hernández Universidad Nacional Autónoma de Honduras. Comayagua, Honduras https://orcid.org/0009-0004-7327-2813

DOI:

https://doi.org/10.58763/rc2024335

Palabras clave:

banco, empleado, inteligencia, inteligencia artificial

Resumen

Este artículo presenta una exhaustiva revisión bibliométrica de 2916 artículos sobre inteligencia artificial en servicios bancarios, extraídos de Web of Science y analizados con VOSviewer. La producción científica en este campo ha experimentado un crecimiento exponencial desde 2016, con Estados Unidos liderando la investigación, seguido de países europeos como Inglaterra y Francia. La colaboración internacional es evidente, y permiten destacar la naturaleza global de la investigación en IA bancaria. Se observa un enfoque significativo en la mejora del riesgo crediticio, con énfasis en la aplicación de la IA para proporcionar explicaciones claras y mejorar la precisión de las evaluaciones del riesgo. La tendencia hacia la personalización y la mejora de la experiencia del usuario es evidente, especialmente en plataformas móviles. Sin embargo, la discusión de diversos estudios destaca desafíos críticos, como sesgos y vulnerabilidades a ataques informáticos. La ausencia de evidencia de producción científica en Centroamérica resalta una oportunidad significativa para fomentar la investigación en esta región. Este análisis bibliométrico proporciona una base sólida para comprender las tendencias actuales y los desafíos en la aplicación de la IA en servicios bancarios, subrayando la importancia de abordar problemas clave para avanzar de manera efectiva en este campo estratégico en evolución.

Métricas

Cargando métricas ...

Citas

Abele, D., y D’Onofrio, S. (2020). Artificial Intelligence – The Big Picture. En Cognitive Computing (pp. 31–65). Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-27941-7_2

Acevedo-Duque, Á., Llanos-Herrera, G., García-Salirrosas, E., ... y Sánchez, L. (2022). Scientometric Analysis of Hiking Tourism and Its Relevance for Wellbeing and Knowledge Management. International Journal of Environmental Research and Public Health, 19(14), 8534. https://doi.org/10.3390/ijerph19148534

Acevedo-Duque, Á., Vega-Muñoz, A., y Salazar-Sepúlveda, G. (2020). Analysis of Hospitality, Leisure, and Tourism Studies in Chile. Sustainability, 12(18), 7238. https://doi.org/10.3390/su12187238

Adamopoulou, E., y Moussiades, L. (2020). Chatbots: History, technology, and applications. Machine Learning with Applications, 2, 100006. https://doi.org/10.1016/j.mlwa.2020.100006

Al-Ababneh, H., Borisova, V., Zakharzhevska, A., Tkachenko, P., y Andrusiak, N. (2022). Performance of Artificial Intelligence Technologies in Banking Institutions. WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS, 20, 307–317. https://doi.org/10.37394/23207.2023.20.29

Alonso, A., y Carbó, J. (2022). Measuring the model risk-adjusted performance of machine learning algorithms in credit default prediction. Financial Innovation, 8(1), 70. https://doi.org/10.1186/s40854-022-00366-1

Alonso-Robisco, A., y Carbó, J. (2022). Inteligencia artificial y finanzas: Una alianza estratégica. Documentos Ocasionales/Banco de España, 2222. https://repositorio.bde.es/handle/123456789/23434

Benbya, H., Davenport, T., y Pachidi, S. (2020). Artificial Intelligence in Organizations: Current State and Future Opportunities. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3741983

Bhattacharya, C., y Sinha, M. (2022). The Role of Artificial Intelligence in Banking for Leveraging Customer Experience. Australasian Business, Accounting and Finance Journal, 16(5), 89–105. https://doi.org/10.14453/aabfj.v16i5.07

Bihari, A., Tripathi, S., y Deepak, A. (2023). A review on h-index and its alternative indices. Journal of Information Science, 49(3), 624–665. https://doi.org/10.1177/01655515211014478

Breeden, J. (2021). A survey of machine learning in credit risk. The Journal of Credit Risk. https://doi.org/10.21314/JCR.2021.008

Brown, T., Park, A., y Pitt, L. (2020). A 60-Year Bibliographic Review Of the Journal of Advertising Research: Perspectives on Trends in Authorship, Influences, and Research Impact. Journal of Advertising Research, 60(4), 353–360. https://doi.org/10.2501/JAR-2020-028

Bussmann, N., Giudici, P., Marinelli, D., y Papenbrock, J. (2021). Explainable Machine Learning in Credit Risk Management. Computational Economics, 57(1), 203–216. https://doi.org/10.1007/s10614-020-10042-0

Cai, Z.-X., Liu, L., Chen, B., y Wang, Y. (2021). Artificial Intelligence: From Beginning to Date. WORLD SCIENTIFIC. https://doi.org/10.1142/11921

Cao, D., y Shao, S. (2020). Towards Complexity and Dynamics: A Bibliometric-Qualitative Review of Network Research in Construction. Complexity, 2020, 1–19. https://doi.org/10.1155/2020/8812466

Chen, D., Ye, W., y Ye, J. (2022). Interpretable Selective Learning in Credit Risk. Research in international business and finance, 1–17.

Corral, Á., y Serra, I. (2020). The Brevity Law as a Scaling Law, and a Possible Origin of Zipf’s Law for Word Frequencies. Entropy, 22(2), 224. https://doi.org/10.3390/e22020224

de Granda-Orive, J., Alonso-Arroyo, A., García-Río, F., … y Aleixandre-Benavent, R. (2013). Certain advantages of Scopus compare with Web of Science in a bibliometric analysis related to smoking | Ciertas ventajas de scopus sobre web of science en un análisis bibliométrico sobre tabaquismo. Revista Espanola de Documentacion Cientifica, 36(2), 1–9. https://doi.org/10.3989/redc.2013.2.941

Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., y Lim, W. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070

Donthu, N., Kumar, S., y Pattnaik, D. (2020). Forty-five years of Journal of Business Research: A bibliometric analysis. Journal of Business Research, 109, 1–14. https://doi.org/10.1016/j.jbusres.2019.10.039

Doumpos, M., Zopounidis, C., Gounopoulos, D., Platanakis, E., y Zhang, W. (2023). Operational research and artificial intelligence methods in banking. European Journal of Operational Research, 306(1), 1–16. https://doi.org/10.1016/j.ejor.2022.04.027

Fernández, A. (2019). Inteligencia artificial en los servicios financieros. Boletín Económico/Banco de España, 2/2019. https://core.ac.uk/download/pdf/322617455.pdf

García-Villar, C., y García-Santos, J. (2021). Bibliometric indicators to evaluate scientific activity. Radiología, 63(3), 228–235. https://doi.org/10.1016/j.rxeng.2021.01.002

Gomes, P., Verçosa, L., Melo, F., ... y Bezerra, B. (2022). Artificial Intelligence-Based Methods for Business Processes: A Systematic Literature Review. Applied Sciences, 12(5), 2314. https://doi.org/10.3390/app12052314

Huang, M.-H., y Rust, R. (2018). Artificial Intelligence in Service. Journal of Service Research, 21(2), 155–172. https://doi.org/10.1177/1094670517752459

Jabeur, S., Gharib, C., Mefteh-Wali, S., y Arfi, W. (2021). CatBoost model and artificial intelligence techniques for corporate failure prediction. Technological Forecasting and Social Change, 166, 120658. https://doi.org/10.1016/j.techfore.2021.120658

Königstorfer, F., y Thalmann, S. (2020). Applications of Artificial Intelligence in commercial banks – A research agenda for behavioral finance. Journal of Behavioral and Experimental Finance, 27, 100352. https://doi.org/10.1016/j.jbef.2020.100352

Korteling, J., van De Boer-Visschedijk, G., Blankendaal, R., Boonekamp, R., y Eikelboom, A. (2021). Human- versus Artificial Intelligence. Frontiers in Artificial Intelligence, 4, 622364. https://doi.org/10.3389/frai.2021.622364

Manser, E., Peltier, J., y Barger, V. (2021). Enhancing the value co-creation process: Artificial intelligence and mobile banking service platforms. Journal of Research in Interactive Marketing, 15(1), 68–85. https://doi.org/10.1108/JRIM-10-2020-0214

Manta, A., Bădîrcea, R., Doran, N., … y Popescu, J. (2024). Industry 4.0 Transformation: Analysing the Impact of Artificial Intelligence on the Banking Sector through Bibliometric Trends. Electronics, 13(9), 1693. https://doi.org/10.3390/electronics13091693

Mhlanga, D. (2021). Financial Inclusion in Emerging Economies: The Application of Machine Learning and Artificial Intelligence in Credit Risk Assessment. International Journal of Financial Studies, 9(3), 39. https://doi.org/10.3390/ijfs9030039

Milana, C., y Ashta, A. (2021). Artificial intelligence techniques in finance and financial markets: A survey of the literature. Strategic Change, 30(3), 189–209. https://doi.org/10.1002/jsc.2403

Misischia, C., Poecze, F., y Strauss, C. (2022). Chatbots in customer service: Their relevance and impact on service quality. Procedia Computer Science, 201, 421–428. https://doi.org/10.1016/j.procs.2022.03.055

Mohamad, S., Salim, N., y Jambli, M. (2021). Service chatbots: A systematic review. Expert Systems with Applications, 184, 115461. https://doi.org/10.1016/j.eswa.2021.115461

Mokhnacheva, Y., y Tsvetkova, V. (2020). Development of Bibliometrics as a Scientific Field. Scientific and Technical Information Processing, 47(3), 158–163. https://doi.org/10.3103/S014768822003003X

Ng, D., Leung, J., Chu, S., y Qiao, M. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, 100041. https://doi.org/10.1016/j.caeai.2021.100041

Noreen, U., Shafique, A., Ahmed, Z., y Ashfaq, M. (2023). Banking 4.0: Artificial Intelligence (AI) in Banking Industry & Consumer’s Perspective. Sustainability, 15(4), 3682. https://doi.org/10.3390/su15043682

Northey, G., Hunter, V., Mulcahy, R., Choong, K., y Mehmet, M. (2022). Man vs machine: How artificial intelligence in banking influences consumer belief in financial advice. International Journal of Bank Marketing, 40(6), 1182-1199. https://doi.org/10.1108/IJBM-09-2021-0439

Osei, L., Cherkasova, Y., y Oware, K. (2023). Unlocking the full potential of digital transformation in banking: A bibliometric review and emerging trend. Future Business Journal, 9(1), 30. https://doi.org/10.1186/s43093-023-00207-2

Pranckutė, R. (2021). Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World. Publications, 9(1), 12. https://doi.org/10.3390/publications9010012

Rahman, M., Ming, T., Baigh, T., y Sarker, M. (2023). Adoption of artificial intelligence in banking services: An empirical analysis. International Journal of Emerging Markets, 18(10), 4270–4300. https://doi.org/10.1108/IJOEM-06-2020-0724

Rajendran, R., Priya T., y Chitrarasu, K. (2024). Natural Language Processing (NLP) in Chatbot Design: NLP’s Impact on Chatbot Architecture. En Advances in Computational Intelligence and Robotics (pp. 102–113). IGI Global. https://doi.org/10.4018/979-8-3693-1830-0.ch006

Ruiz-Real, J., Uribe-Toril, J., Torres, J., y de Pablo, J. (2020). ARTIFICIAL INTELLIGENCE IN BUSINESS AND ECONOMICS RESEARCH: TRENDS AND FUTURE. Journal of Business Economics and Management, 22(1), 98–117. https://doi.org/10.3846/jbem.2020.13641

Sadok, H., Sakka, F., y El Maknouzi, M. (2022). Artificial intelligence and bank credit analysis: A review. Cogent Economics & Finance, 10(1), 2023262. https://doi.org/10.1080/23322039.2021.2023262

Sahu, A., y Jena, P. (2022). Lotka’s law and author productivity pattern of research in law discipline. Collection and Curation, 41(2), 62–73. https://doi.org/10.1108/CC-04-2021-0012

Sánchez, V., Pérez, A., y Gómez, C. (2024). Trends and evolution of Scientometric and Bibliometric research in the SCOPUS database. Bibliotecas, Anales de Investigacion, 20(1). http://revistas.bnjm.sld.cu/index.php/BAI/article/view/834

Su, Y.-S., Lin, C.-L., Chen, S.-Y., y Lai, C.-F. (2019). Bibliometric study of social network analysis literature. Library Hi Tech, 38(2), 420–433. https://doi.org/10.1108/LHT-01-2019-0028

Umamaheswari, S., y Valarmathi, A. (2023). Role of artificial intelligence in the banking sector. Journal of Survey in Fisheries Sciences, 10(4S), 2841–2849. https://doi.org/10.17762/sfs.v10i4S.1722

Valverde, S., Solas, P., y Fernández, F. (2023). Algunas reflexiones sobre la inteligencia artificial en el sector bancario. Cuadernos de Información económica, 295, 35–40.

Vargas, A https://doi.org/10.15381/idata.v24i2.20351. (2021). La banca digital: Innovación tecnológica en la inclusión financiera en el Perú. Industrial Data, 24(2), 99-120. https://doi.org/10.15381/idata.v24i2.20351

Wang, X., Lin, X., y Shao, B. (2022). How does artificial intelligence create business agility? Evidence from chatbots. International Journal of Information Management, 66, 102535. https://doi.org/10.1016/j.ijinfomgt.2022.102535

Xu, Y., Shieh, C.-H., Van Esch, P., & Ling, I.-L. (2020). AI Customer Service: Task Complexity, Problem-Solving Ability, and Usage Intention. Australasian Marketing Journal, 28(4), 189–199. https://doi.org/10.1016/j.ausmj.2020.03.005

Zarifis, A., y Cheng, X. (2022). A model of trust in Fintech and trust in Insurtech: How Artificial Intelligence and the context influence it. Journal of Behavioral and Experimental Finance, 36, 100739. https://doi.org/10.1016/j.jbef.2022.100739

Zhang, C., y Lu, Y. (2021). Study on artificial intelligence: The state of the art and future prospects. Journal of Industrial Information Integration, 23, 100224. https://doi.org/10.1016/j.jii.2021.100224