I would like to build a scorecard from scratch.
Currently I have been working on data cleaning, and I created a dataset for training and another for test. What I have is a dataset of around 700 rows (maybe not so many as I could expect; it is for a computer science project), 20 columns. The target is if the borrower has defaulted or not (indicator). Most of the factors are categorical or Boolean. I am assigning a score based on these parameters, specifically:
- if the account has defaulted in the last 90 dats, then assign 60; - if the account has defaulted in the last 30 days, then assign 50; - if the account has not defaulted in the last 90 days, then assign 80; ...
I would like to know if this is a good approach and/or if there is an algorithm to assign scores to the accounts or if I should do something different. I do not know very well the logic behind a scorecard, so any information would be extremely useful.