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Previous issue date: 2016-03-10 === Similarities of products and services, market stagnation, the portability of operations among institutions, competition and competitiveness in banking sector have motivated more attention to customer loyalty. It is essential to win new clients as well as to retain them in order to avoid churn. So management tools that concern relations with customers require an increasing amount of variables. Present study covers the best clients in a big-size Brazilian financial institution. It proposes a model for churn predicting, based on the evolution of their loans and investments. Operations from ca. 291 thousands clients were the input data for software QlikView (a user-oriented Business Intelligence platform). The model transformed the Daily Balance Average into a logarithm scale in order to assess the value oscillation according to periods. The achieved index seems to be a possible churn predictor, which indicates that relations management should regard carefully customers susceptible to churn. Nevertheless this index alone does not explain the churn rate. It is recommended to apply it as a complement and a refinement of other indexes that are already deployed in customer loyalty management. === As semelhan??as de produtos e servi??os, a estagna????o do mercado, a portabilidade de
opera????es entre institui????es e a concorr??ncia e competitividade no setor banc??rio t??m
motivado mais aten????o ?? fideliza????o do cliente. A considera????o de tais fatores ?? essencial
para a conquista de novos clientes, bem como para a sua reten????o, a fim de evitar o churn.
Assim, ferramentas de gest??o de relacionamento com o cliente exigem uma quantidade
crescente de vari??veis. O presente estudo abrange os melhores clientes de uma institui????o
financeira brasileira de grande porte. Prop??e um modelo para a predi????o de churn, com base
na evolu????o dos seus empr??stimos e investimentos. Opera????es de 291.761 clientes foram os
dados de entrada para a ferramenta QlikView (uma plataforma de BI ??? Business Intelligence
??? orientada ao usu??rio). O modelo transformou a M??dia de Saldos Di??rio (MSD) em uma
escala logar??tmica, a fim de avaliar a oscila????o de acordo com os per??odos. O indicador
alcan??ado parece ser um poss??vel preditor de churn, o que indica que a gest??o de
relacionamento deve considerar cuidadosamente os clientes suscet??veis ?? evas??o. No entanto,
s?? este indicador n??o explica a taxa de churn. Recomenda-se aplic??-lo como um
complemento e um refinamento de outros indicadores que j?? est??o implantados na gest??o da
fideliza????o com o cliente.
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