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Hi guys..I am working on a logistic model. When I did out of sample validation, my percentage detection of the defaulters was 80%. The next I tried is out of time validation. To my dismay the accuracy(percent detection) came down to 33% this time. I am wondering and disappointed by what could have happened. I have profiled both the population and found differences in the distribution of few categorical variables.
Please pour in your ideas as to what can be done to improve the accuracy in the out of time dataset or what could have gone wrong. If required to defend before the client, what justification can one give for the downfall in accuracy ?