Saltar al contenido
República del Perú · Observatorio de la producción científica universitaria
OApol.org Observatorio de Inteligencia Científica Universitaria del Perú
OApol.org
Inicio Universidades Publicaciones Investigadores
Repositorios
Tesis y trabajos académicosRevistas
Indicadores
Ranking trimestralRanking por carreraObjetivos de Desarrollo SostenibleReporte OCDERed neuronal 3D
Acerca
MetodologíaPrivacidad

Advances in the use of artificial intelligence to improve control and fraud detection in organizations

Lescano-Delgado M. · Revista Cientifica de Sistemas e Informatica (2023) · DOI: 10.51252/rcsi.v3i1.494

Resumen

The study reviewed the use of artificial intelligence (AI) to improve fraud control and detection in organizations, based on 31 scientific articles published between 2020 and 2022. Key technologies include machine learning, deep learning, and blockchain, which have been shown to improve the accuracy of fraud detection and optimize the handling of large volumes of data. These tools not only improve internal controls, but also reinforce the security and transparency of transactions, mainly in the financial and business sectors. The results suggest that these technologies reduce false positives and improve real-time detection. However, challenges are identified, such as interoperability between systems and staff training. In conclusion, the adoption of AI in fraud detection is a growing trend that offers advanced solutions, although challenges remain to maximize its long-term impact.

Instituciones: Universidad César Vallejo