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Pondera FraudCast

Welcome to the Pondera FraudCast, a weekly blog where we post information on fraud trends, lessons learned from client engagements, and observations from our investigators in the field. We hope you’ll check back often to stay current with our efforts to combat fraud, waste, and abuse in large government programs.

Identity Theft: Steal Once, Use Often

Identity Theft: Steal Once, Use Often

A recent arrest in New York City illustrates a common fraud method that Pondera has been talking about for years: falsifying an identity (of an individual or business) and using it across multiple states, or in this particular case, across multiple subsidy programs within a state.

In February of this year, the New York State Attorney announced the arrest of several individuals allegedly involved with a fraudulent medical supply company. The company’s owner operated under a false social security number and billed the State Medicaid system for an expensive nutritional formula required by patients with feeding tubes. In actuality, when they delivered the service at all, they dispensed lower-priced Pediasure to dramatically increase their profits—apparently ignoring the health consequences to the patient.

But, as is often the case with bad actors, they didn’t stop there. In addition to their fraudulently obtained Medicaid profits, the fraudsters also used their fake socials and claimed income of less than $800 per month in order to qualify for Welfare payments. This despite the fact their medical “business” incomes were over $180,000 per year. It would not surprise me to learn that these same people were operating in other subsidy programs or in neighboring states.

This is a disturbing, but somewhat logical, pattern that we see again and again. When someone goes to the trouble of creating a fake identity or business, they use it to generate as much income as possible. They “fly below the radar” of each individual program (or state) to avoid detection, but the fraud can be very lucrative in aggregate.

The obvious solution to this is increased cooperation and data sharing across programs within a state and across states. The federal government has made significant efforts to support data sharing including the List of Excluded Individuals and Entities (LEIE), the Death Master File, and the Prisoner Update Processing System (PUPS) which can help identify claims that are fraudulently made by ineligible, deceased, or incarcerated identities.

Our hope is that these efforts expand, including at the state level, where multiple agencies cooperate to identify cross-program fraud schemes. It is not enough to detect and then stop individual incidents of fraud. Many of these incidents are too small, when viewed as discrete occurrences, to warrant prosecution. Knowing this, enterprising fraudsters “sprinkle” their claims across multiple jurisdictions to avoid attention.

Unfortunately, as was the case in New York, even these smaller, distributed fraud efforts can have an impact on patient health. The good news is that New York detected and put an end to this incident. But we all know there are thousands of similar cases each year.
Congress Turns its Attention to SNAP Trafficking Fraud

Congress Turns its Attention to SNAP Trafficking Fraud

A few months ago, I wrote an article offering our support to the USDA Food and Nutrition Service (FNS) as it rolls out a new program offering online access to groceries for Supplemental Nutrition Assistance Program (SNAP) recipients. My main concern with the new initiative was that FNS cannot provide an accurate SNAP fraud rate because of unreliable data coming in from the states. And we all know that offering goods and services online presents even more opportunities for fraud.

Now Congress is asking FNS additional questions in a letter sent to them on February 8th. Outlining the lawmakers’ concerns, the letter points out that as many as 10% of retailers who accept SNAP EBT cards participate in illegal trafficking schemes. These schemes pay recipients a discounted amount of cash or unapproved grocery items in exchange for their cards. They go on to point out that total annual fraud in the program is over $858 million.

The massive size of the SNAP program is one of the major reasons, historically at least, it is so difficult to detect fraud. In 2016, the program distributed $67 billion in benefits to 44 million Americans through 260,000 authorized retailers. Interestingly though, as much as 85% of the retailer fraud is committed by small grocery and convenience stores, or even flea markets like the one in Opa-Locka, FL that we recently wrote about.

With the advent of cloud computing and advanced analytics solutions, FNS now has access to the tools required to make a real difference in their fight against fraud. And by addressing the retailer side of the equation, they will also find, through association, many of the fraudulent individuals in the system as well. It would certainly make sense for FNS to leverage modern fraud detection technologies at the same time that they offer online access to groceries.

It is also important to note that the number of SNAP program retailers and recipients, while large, is very manageable. Consider that at Pondera we’ve performed equally complex fraud analytics on Medicaid programs with as many as 200,000 providers and Unemployment Insurance systems with over 1,000,000 employers. And when one considers that the overwhelming majority of SNAP trafficking fraud occurs in a concentrated subsection of small and medium retailers, the problem becomes even more manageable.
What do Competitive Running and Fraud Detection Have in Common?

What do Competitive Running and Fraud Detection Have in Common?

I read with great interest the story this month about a woman who cheated her way to a second-place finish in the Fort Lauderdale half marathon. After posting a time of 1 hour and 21 minutes, the website www.marathoninvestigation.com revealed several problems with the woman’s results including: the race statistics she posted to a website were manually entered (versus those calculated by her GPS), a second set of results she posted seemed more consistent with a bike ride, and a zoomed photo of her post race wristwatch revealed that she ran only 11.65 miles of the 13.1 mile race. This evidence led to an admission and apology by the runner.

What I find interesting about this incident is how indicative it is of the ever-increasing power of data. While runners collect data to help them train and perform better, it can also be used to uncover cheating and fraud. This is no different in government subsidy programs, like Medicaid and welfare systems. Governments collect data to help them improve service delivery to their constituents, and with modern technologies, the data can also reveal fraudulent anomalies and patterns.

Of course, bad actors who want to defraud programs are aware of the increased use of data to catch them. Gone are the days when they can blatantly abuse government systems knowing that the size and complexity of the programs would make it nearly impossible to catch the cheats. In running, who would dare to repeat Rosie Ruiz’s 1980 Boston Marathon “victory” where she was spotted riding the subway with her runner’s bib?

Instead, bad actors often “fly under the radar” – stealing smaller amounts over longer periods of time to avoid being noticed. Second place in the Fort Lauderdale Marathon is certainly “under the radar” compared to a victory in the Boston Marathon.

So, now that our fraud detection capabilities can catch bad actors who boldly fly above the radar and those who strategically fly below the radar, one would hope that it would lead to decreases in fraud attempts. But I also know that making fraud harder to commit rarely turns fraudsters into honest and contributing members of society. It just makes them work harder. This simple fact provides us with the incentive to continually improve on our technologies and approaches. This is one war we fully intend to win.

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Pondera leverages advanced prediction algorithms and the power of cloud computing to combat fraud, waste, and abuse in government programs.



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