Keycorp Limited

Luke Tetreault

Dale Bonds

John W Burgess

A method and system for processing financial instruments to detect the presence of duplicate instruments. The method may include the steps of receiving items of information for a plurality of financial instruments, grouping the items into cycles and appending cycle and time dependent information to the items to form coded items, storing the coded items in a database, comparing the items to find items having duplicate identifying information, marking duplicate items for subsequent deletion and printing a report listing the duplicate items. The system may include a mainframe, data repository, item processing applications, and a module that filters items from incoming strings to remove false positives. The remaining duplicate items may be viewed on a graphical user interface that allows a user to review attributes of each item and manually mark duplicates for subsequent deletion.

System and method of financial instrument processing with duplicate item detection

A method and system for processing financial instruments in order to detect the presence of duplicate instruments. The method may include the steps of receiving discrete items of identifying information, each for a plurality of financial instruments, grouping the items into cycles and appending discrete cycle and time dependent information to each of the items to form coded items, storing each of the coded items in a database, comparing the stored, coded items to each other to find items having duplicate identifying information, marking items having duplicate identifying information for subsequent deletion and printing a report listing all items having duplicate identifying information. The system may include a mainframe, data repository and item processing applications, all interconnected by a network. The system may receive discrete items of identifying information over a network, such as the Internet or private network, such as SVPCO. In a preferred embodiment, the system may include a module that filters items from incoming strings of items to remove false positives, namely, those items that might otherwise appear to be duplicates, but in fact are not, such as rebate coupons. The remaining duplicate items may be viewed on a graphical user interface that allows a user to review attributes of each item and manually mark duplicates for subsequent deletion.

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Loudonville, NY, United States of America

Luke Tetreault