Box Jenkins Method Applied to forecast the Federal Savings Bank monthly demand of Clients

• Autor(a) principal: da Silva, Jonas Ferreira
• Data de Publicação: 2023
• Outros Autores: Nepomuceno, thyago Celso Cavalcante, Rodrigues, Naialy Patricia
• Tipo de documento: Artigo
• Idioma: por; eng
• Título da fonte: Diversitas Journal
• Texto Completo: https://diversitasjournal.com.br/diversitas_journal/article/view/2517
• topic: Análise de Dados, Econometria de Séries Temporais, ARIMA, Modelos de Previsão, Banco, Caixa Econômica Federal; Previsão de dados; Analise de dados; Modelo ARIMA; Análisis de Datos, Econometría de Series Temporales, ARIMA, Modelos de Pronóstico, Banco, Caixa Econômica Federal; Data Analysis, Time Series Econometrics, ARIMA, Prediction Models, Banking, Brazilian Federal Savings Bank

Queue management in the banking service is a current and recurring challenge that service units face daily in modern times, and especially in Caixa Econômica Federal branches, due to their profile and social mission, this problem is quite relevant as it affects the quality of lives of customers and employees, leading to effects at scale where simple demands can result in hours of waiting, a situation even more critical considering the current pandemic and post-pandemic context. The present work aims to estimate the service demand in a typical branch of Caixa Econômica Federal (CEF) for strategic planning and distribution of resources over time and sectors of the bank. Data were collected on the times and quantities of service in the years 2019 and 2020. After collection, the data were processed and the Jenkins box methodology was applied to find the best forecast models for the data reported by the establishment.