$279 Million No-Fault Auto Insurance Scam In NYC Called Largest Ever
A cadre of corrupt doctors and scam artists sought to cheat auto insurance companies out of $279 million in bogus medical claims — the largest-ever fraud involving New York’s no-fault law, authorities said Wednesday.
The investigation resulted in federal racketeering, health care fraud, mail fraud and money laundering charges against 36 people, mainly of Russian descent. They include 10 physicians and three lawyers. One had the nickname “KGB.”
At a news conference, U.S. Attorney Preet Bharara said while the false claims totaled $279 million, the actual loss to private insurers was $113 million. Some of the ill-gotten gains were spent on vacations in Mexico, shopping sprees at Saks Fifth Avenue and rides in limousines, he said.
read more...A $250 Million Fraud Scheme Finds a Path to Brighton Beach
The plot involved 10 doctors, 9 separate clinics in New York City and 105 different corporations, all in service of a health care fraud ring that federal authorities say conspired to steal more than a quarter of a billion dollars from insurance companies. And when the details were announced on Wednesday, they cast an unflattering spotlight on how immigrants from the former Soviet Union have often dominated such schemes in the city.
This one, like many others, was rooted in Brighton Beach, Brooklyn, the locus of the city’s Russian-speaking immigrant population, many of whom grew up under a Communist system that bred disdain for the rules and a willingness to cheat to get around them.
Brighton Beach has one of the highest rates of health care fraud in the nation, according to federal statistics. In fact, an analysis of data from the Centers for Medicare and Medicaid Services, the federal agency that regulates those two programs, shows that more health care providers in the Brighton Beach ZIP code are currently barred from the programs for malfeasance than in almost any other ZIP code in the United States. (The top spot is in southern Florida, with its high proportion of older residents.)read more...
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