Professional criminal enterprises inflict more damage and losses on society than opportunistic individuals. Yet today, anti-fraud program managers focus primarily on detecting outliers, researching standalone fraud events and acting on tips. And why not? Most anti-fraud analytic methods are focused at the provider or claim level; very little – if any – advanced data analysis focuses on the detection of collusive behavior among multiple entities. The criminal enterprises that exploit agencies providing everything from government loans to subsidized housing to food stamps know that antifraud investigators struggle to connect the dots – and fraudsters use this to their advantage. While law enforcement gets distracted with the latest fraud scheme, professional fraud organizations constantly change their tactics – finding their way back into the system after being kicked out for fraudulent behavior or always staying one step ahead of the “pay-andchase” game.
This paper will explore how your law enforcement or government agency can use multiple analytical methods to proactively identify crime rings in their infancy – and spare federal taxpayers billions of dollars misspent on spurious benefits payouts each year.