A Temporal Approach to Customer Churn Prediction: A Case Study for Financial Services

  • Marcus Almeida UFOP
  • Mariana Mota UFOP
  • Wellington Souza Gerencianet S.A
  • Marcos Nicolau Gerencianet S.A
  • Eduardo Luz UFOP
  • Gladston Moreira UFOP

Resumo


Modelos de previsão de desligamento de clientes visam detectar clientes com alta probabilidade de cancelamento do contrato, com base no uso dos serviços oferecidos. Propomos uma abordagem temporal para a etapa de rotulagem, baseada na redução da frequência de uso dos serviços, por meio do comportamento de cada cliente. Também propomos uma arquitetura de rede neural temporal para a tarefa. A abordagem foi avaliada em um conjunto de dados reais, fornecido por uma empresa brasileira do setor financeiro. A rede neural convolucional temporal alcançou uma acurácia de 82, 63%, uma sensibilidade de 61, 5% e uma precisão de 41, 58%, superando outros classificadores tradicionais (XG-Boost e Floresta Aleatória).

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Publicado
28/11/2022
ALMEIDA, Marcus; MOTA, Mariana; SOUZA, Wellington; NICOLAU, Marcos; LUZ, Eduardo; MOREIRA, Gladston. A Temporal Approach to Customer Churn Prediction: A Case Study for Financial Services. In: ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL (ENIAC), 19. , 2022, Campinas/SP. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2022 . p. 83-94. ISSN 2763-9061. DOI: https://doi.org/10.5753/eniac.2022.227571.

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