I am a beginner and my question relates to feature engineering. My task is to help develop a model which predicts whether a customer request is a fraud case.
A variable in the dataset is the applicant's zip code. Is it ok to create an indicator variable which is 0 if fraud does not happen frequently (e.g. <2% fraud) for this postal code and 1 otherwise? Or is this wrong because I would use the dependent variable (isFraud) to find out in which places fraud happens frequently and falsify the result?
Any help would be greatly appreciated!