USCIS Improves Fraud Analytics with Senzing Entity Resolution
White Paper: How USCIS Utilized Senzing Entity Resolution to Improve Fraud Analytics
The United States Citizenship and Immigration Services (USCIS) needed to improve its ability to identify immigration fraud committed by applicants and their representatives. The project involved detecting relationships between individuals requesting asylum or entry into the country and their lawyers and other representatives.
The USCIS development team was working with many complex source systems and data models containing duplicate names and addresses as well as human-induced errors. Unique identifiers were also different between sources, and some sources lacked identifiers for certain record types.
USCIS Project Goals
USCIS Selected Senzing Entity Resolution for Fraud Detection
After evaluating several options, the USCIS team selected Senzing® entity resolution as the data matching and relationship detection component of its solution. With Senzing entity resolution, USCIS is able to identify more fraud, improve the quality of insights and the user experience of its fraud analysts, and realize significant cost reductions.
