08-23-2016 03:30 AM - edited 08-23-2016 03:32 AM
I am building a retail customer attrition model for saving accounts of a bank. I am targeting both soft and hard attrition (Dependent Variable).
By 'soft attrition', i mean if saving balance drops by 80% or more. By 'hard attrition', i mean customer closes his account.
My question - can i use % balance change as a predictor/ independent variable in the model. Since i am already taking customers having 80% or more balance dropped as an event in the dependent variable, would it be right to use the % change as an independent variable in the model?
08-23-2016 03:51 AM
What kind of model are you using ? If it is logistic model , I think you can use % balance change as Y . For example: data have; set have; retain n 1; per_balance_change=.........; run; proc logistic ........... model per_balance_change/n = ...........; You can take HARD as per_balance_change=1 .
08-23-2016 06:04 AM
As long as the information predates your knowledge of their attrition. So perhaps % change in prior month?
Using it over same period as your definition of dependent would be incorrect as then this is Informatiom is after the fact.
08-23-2016 06:14 AM
80% drop from where? Maximum all time balance? Previous three months? As @Reeza says, you might want to introduce a lagged variable (3 or 6 months?) to help you formulate this model.
08-23-2016 08:58 AM
Thanks everyone for your response. @Rick_SAS and @Reeza - Yes, it's 80% drop from maximum all time balance. I have considered it as a target variable. Can i use % balance change from maximum all time balance as an independent variable? If i am not wrong, you are suggesting i can use % change in 3 months or 6 months as independent variables, not % balance change from maximum all time balance.
08-23-2016 09:05 AM
SAS will enable you to build either model. I don't have any intuition about which will perform best, so I will leave that modeling decision to you. You can test multiple models on historial data and choose the one that performs the best.