Machine learning application for campaigns marketing in commercial banking

• Autores: Rosales Reyes, Ganímedes T., Gutierrez Coral, Xavier Alberto, Hayashida Marchinares, Augusto Enrique
• Formato: artículo
• Fecha de Publicación: 2022
• Institución: Universidad de Lima
• Repositorio: Revistas - Universidad de Lima
• Lenguaje: español
• OAI Identifier: oai:revistas.ulima.edu.pe:article/5953
• Enlace del recurso: https://revistas.ulima.edu.pe/index.php/Interfases/article/view/5953
• Nivel de acceso: acceso abierto
• Materia: banking; marketing; fixed-term deposits; machine learning; classification algorithms; banca; depósitos a plazo fijo; aprendizaje automático; algoritmos de clasificación

Banks use telemarketing to contact potential customers for their products directly. This sales channel is complex, requiring large databases of possible prospects, and is subject to time and personnel restrictions. This article has three objectives: to compare five prediction models based on machine learning algorithms to find the one that offers the best predictive accuracy, deploy a pilot of this model, and recommend a roadmap for the future architecture that supports it. The comparison results show that the selected algorithm considerably improves the identification of customers who accept the product, which went from 11 % to 94 %, so its implementation can contribute to the competitiveness of these organizations.