Binary classification with a TIME variable? I have a dataset to predict whether applicants default on a loan.
Within the dataset, I have a DURATION variable that works as a time variable so I could perform survival analysis.
The thing is, I want to know if I could use a classification model and not survival analysis on the data to predict DEFAULT. Thoughts?
...or can survival analysis be used to predict binary: someone defaulted/did not default?

A binary (e.g., logistic) regression (perhaps as a precursor to later classification) could work if you have complete data covering the exact same period of time for all cases. Then you would model the probability of default over that specific period of time.
In general, though, if you have time information available it's best to do survival analysis. That way you can predict the probability of default as a function of both time and covariate values. That provides more flexibility in downstream use of your model. For example, with time information you could model the actual expected loss by combining the estimated time to default with the payments up through that time point. A simple defaulted/didn't binary model can't do that.
