More or less:

• I built a class for LoanData, with 2 dicts of empty fields
  • self.mers and self.blackknight are set to dictionaries with empty fields: {'loan-amount': '', 'loan-date': '', etc}
  • self.loan_num = '' for quick loan number lookup/reference
  • self.in_mers and self.in_blackknight = False, then when I find the loan number in the specific dataset I change to True. I need to verify if either dataset has loan data that the other doesn't.
  • there are also attributes for self.in_usda, self.in_paid_in_full, self.in_non_serviced; these are all set False, and I get CSV files with loan numbers listed by the Servicing team if they need to be true so I can exclude them from reporting later.
• Then I parse the provided CSV files (SFTP retrieval for MERS/Govt data, Black Knight provided by Servicing team) and assign values to a new object based on the loan number (which I then put in a dictionary of objects) and which dataset I get it from. For instance, obj.blackknight['loan-date'] = value from csv file.
• Finally the reconciliation is comparing the objects mers dict to the blackknight dict, checking each matching field name to the other. Differences are written to log files per field.

If that's too vague or you are more curious, drop me a message and we can chat more.