Fuzzy match: A fuzzy match occurs when new user data closely resembles an existing record but is not identical, flagging the possibility of a duplicate identity. Identifying and resolving these matches prevents duplicate accounts, contact errors, and security issues. 

Identifying a fuzzy match: UCSF systems use sophisticated matching algorithms to scan new user records against existing ones. These algorithms compare key fields (e.g., name, date of birth, SSN, email address) and assign a similarity “score” to each match.
 
Records with high similarity, but not exact matches, are flagged for manual review.

Review the quick reference guide, if you would like more details on the fuzzy match process and scoring algorithm.