Every day there are news stories of fraud perpetrated against federal government programs. Topping the list are Medicaid and Medicare schemes which costs taxpayers an estimated $100 billion a year. Fraud also is rampant in other important federal programs, including unemployment and disability benefits, health care, food stamps, tax collection,
When it comes to fraud detection and risk mitigation, predictive modeling has earned a reputation as the “heavy hitter” in the realm of data analytics. As our celebration of International Fraud Awareness Week continues, I would challenge our readers to ask themselves this question, “Is the reliance upon predictive analytics
Another day, another scam defrauding insurers and governments. For purposes of full disclosure, the case I'm highlighting today comes from Washington's Labor and Industries (L&I), the agency where I formerly worked and headed up fraud prevention efforts, and the investigation dates back to my time there. During my time there,
Sometimes, it is good to start with a confession. I filed my taxes at the last minute. It was past time to get some money back from the IRS before they could waste $60,000 on another Star Trek spoof video. Normally I'm one of those people that files in February,
Personally, I love studies. They help put things into context, and when done well, provide an independent and hopefully unbiased view of the forces that shape our lives. They are also a great way to see government funds used in strange ways. For example, the new NIOSH (National Institute for
The first step is to answer the question of what “real-time” actually means. Depending on the program and industry speed of response, I’ve heard answers that varied from milliseconds for the biggest banks in processing credit card charges to 24 hours for some government programs. A better description of what
Fraud detection presents myriad analytical challenges: gathering sufficient known cases to make typical modeling techniques possible, gathering inputs from disparate data sources, and combining expert knowledge from investigators with findings to be gleaned from the data in an efficient way. Of course, analysts can fall into the trap of thinking
Most health care organizations either intentionally or due to some inability don’t use outside information (not just referals) in their search for fraud. There are great numbers of valid reasons for this: HIPAA, security, usable/current data sources, inflexible information systems or processes, restrictive compliance & IT departments, and the list
In the health care field, the impact of fraud, waste and abuse on payers -- whether insurance companies, government agencies or self-insured employers -- is enormous. Fraud losses weaken a payer’s financial position, with fraud loss estimates rivaling net income. Fraud losses feed the escalating care cost curve, undermining a
