Avances en el uso de inteligencia artificial para la mejora del control y la detección de fraudes en organizaciones
DOI:
https://doi.org/10.51252/rcsi.v3i1.494Palabras clave:
aprendizaje automático, análisis de datos, auditoría, ciberseguridad, sistemas automatizadosResumen
El estudio revisó el uso de inteligencia artificial (IA) para mejorar el control y la detección de fraudes en organizaciones, basándose en 31 artículos científicos publicados entre 2020 y 2022. Las tecnologías clave incluyen machine learning, deep learning y blockchain, que han demostrado mejorar la precisión en la detección de fraudes y optimizar el manejo de grandes volúmenes de datos. Estas herramientas no solo mejoran los controles internos, sino que también refuerzan la seguridad y transparencia de las transacciones, principalmente en los sectores financiero y empresarial. Los resultados sugieren que estas tecnologías reducen falsos positivos y mejoran la detección en tiempo real. No obstante, se identifican desafíos, como la interoperabilidad entre sistemas y la capacitación del personal. En conclusión, la adopción de IA en la detección de fraudes es una tendencia en alza que ofrece soluciones avanzadas, aunque persisten retos para maximizar su impacto a largo plazo.
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