Abstract: A method and system for managing of exceptions during reconciliation of transactions, wherein the exceptions are raised for possible mismatches existing between data sets being compared. The reconciliation includes performing a first matching of the two sets based on a predefined rule set and a preset reconciliation type, wherein the first matching raises the exceptions. Further, the exceptions, as a batch file, are processed by performing a second matching for the exception-data based on pattern matching mechanism that utilizes fuzzy logic. The pattern matching mechanism is provided with metafiles corresponding to each batch element of the batch files. Further, only possible close matches are retrieved based on a predefined confidence score threshold. The close matches along with corresponding confidence score may be provided to a user on a User is Interface (UI) for further investigation of the exceptions.

Abstract: A method and system for managing of exceptions during reconciliation of transactions, wherein the exceptions are raised for possible mismatches existing between data sets being compared. The reconciliation includes performing a first matching of the two sets based on a predefined rule set and a preset reconciliation type, wherein the first matching raises the exceptions. Further, the exceptions, as a batch file, are processed by performing a second matching for the exception-data based on pattern matching mechanism that utilizes fuzzy logic. The pattern matching mechanism is provided with metafiles corresponding to each batch element of the batch files. Further, only possible close matches are retrieved based on a predefined confidence score threshold. The close matches along with corresponding confidence score may be provided to a user on a User is Interface (UI) for further investigation of the exceptions.