“Data mining technology that looks for hidden patterns in data such as welfare applications and reports to identify duplication and fraud in services including welfare, healthcare, in-home support services and food stamps. It can predict fraud based on characteristics and circumstances associated with fraudulent activity, such as relationships among parties participating in suspicious activities, unusually large distances between work and home addresses, and inconsistencies in the information reported to eligibility workers.
On October 6, 2009, Supervisors Antonovich and Knabe co-authored a motion to identify the necessary matching county funds to free nearly $10 million dollars in state funding appropriated to the County to combat fraud in the in-home supportive services program. The County’s plan includes the use of data mining.