6 March What do Competitive Running and Fraud Detection Have in Common? March 6, 2017By Jon Coss - Blog Manager government fraud prevention Data, Fort Lauderdale, Fraud 0 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. Related Posts What the Election Means to Fraud Detection It’s only been a few hours since the election of Donald Trump, and we are already fielding questions about what this all means to Pondera. And while I must confess, like most Americans the election result was a bit of a surprise to me, we have been preparing for change no matter who won the election. This is because any change in administration leads to changes in priorities.If I think back only a decade or so, active government program initiatives included Real ID laws for driver licenses, modernizing voter systems, and prison offender management systems. The Obama administration shifted a lot of focus and funding to Medicaid systems, insurance exchanges, and other health and human services programs.What will the Trump administration mean to a fraud detection company like Pondera? While it’s still too early to tell, President-elect Trump has certainly provided some clues. For example, in one campaign speech he proposed funding his childcare initiatives by targeting fraud in state Unemployment Insurance Programs. And anyone who has been paying attention to the news recently could reasonably expect that voter fraud and the Affordable Care Act will receive some attention over the coming months.Here is one thing that I know for certain. Come January, fraud will continue to be perpetrated against government programs no matter what party or which candidate is in charge. To fraudsters, large government programs are considered a target-rich environment too large to ignore. Why It’s Important To Be Nimble When Fighting Fraud Fighting fraud is an interesting challenge. When an organization shuts down a fraud scheme, bad actors don’t suddenly become good citizens. Rather, they evolve. They evolve by designing and testing new methods that, when they succeed, are exploited until they too are detected and shut down. In fact, many of the more enterprising fraudsters proactively try out new methods to avoid any “breaks in revenue”. This constant game of “whack-a-mole” is well known to program integrity staffs.This ever-changing nature of fraud schemes demands an ever-changing detection system. If an organization’s fraud detection methods look more or less the same as they did the year before, I can almost guarantee you that their fraud rates have returned to the levels prior to the introduction of the detection systems. Bad actors will simply find another way to conduct their business.For these reasons, it is important to be nimble in fighting fraud. Complex technologies and massive data warehouses will lose effectiveness over time. If it takes a year to negotiate a change order, to deploy new technologies, or to integrate new data sources, literally billions of dollars in improper payments can be lost. The trick is to stay even with or just a “step” behind the bad actors, not miles behind.While all state agencies want to choose the right partner to help them with their fraud detection efforts, I would challenge them to ask themselves the following questions: How easy is the company to work with? How willing will they be to incorporate new technologies (even if not their own)? How important is fighting government fraud to their company versus everything else they do? How passionate are they about the problem? Honest answers to these questions will reveal a lot about the future success of your efforts. Ugly Case of Health Care Fraud A few weeks ago, I published a blog post titled “Money Obtained Fraudulently is Rarely Used for Good Purposes”. In it, I made the argument that government fraud is a serious, and at times very ugly problem. Now I no longer have to make that argument because the United States Justice Department is making the argument for me.Last week, the Justice Department announced the largest health care fraud case it’s ever prosecuted; one that defrauded over $1 billion over the past 14 years. The alleged perpetrators of the fraud are said to have leased private jets and chauffeured limousines. One even bought a $600,000 watch! Remember, this is your tax money we’re talking about. The system ran on a complex network of bribes and kickbacks.And if that’s not enough, here is one of the schemes they allegedly ran. They “treated” seemingly healthy, elderly people with medications they did not need in order to create addictions which would lead to further treatments. Pure evil. Unfortunately, fraudsters are most active where large amounts of money meet vulnerable populations. This is yet another example of that and more reason for us to do what we do. 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. Binary Nature of Fraud Big data analytics and the predictive engines they spawned give Internet companies a way to monetize the online experience. By tracing online behavior, companies can target advertising, promotions, and point of sale opportunities based upon past buying decisions. Online habits of Web users can be associated with ideologies, interests, and values. Increasingly sophisticated probability engines predict future buying decisions with enough accuracy to fuel a dramatic increase in online sales and commerce over the past decade. Analysts use temporal versions of these tools to forecast market trends and evaluate risk.In the fraud detection market however, early attempts to detect fraudulent behaviors using these same probabilistic engines have achieved limited success.What makes detecting fraud different than detecting interests, values, and ideologies? The simple answer: Fraud is binary in nature–either a particular sequence of behaviors is fraud or it is not. For example, if an individual provider of medical services submits claims to an insurance company for 5,000 hours of services in a week (an instance from actual data), there had better be around 100 employees licensed to provide that service. If there are only three or four employees with the required licenses, the provider has committed fraud. Probabilistic engines struggle to detect fraud because they are not capable of modeling this“all or nothing”nature of violating a law.At Pondera, we still make use of predictive analytics. But rather than detecting absolute fraud, we use the algorithms mostly to inform our fraud scores and to detect emerging fraud methods.Once reliable methods of detecting fraud have been developed, predictive engines can also play an important part in helping insurance companies, financial institutions, and government agencies prioritize targets of investigation. Predictive models can identify the highest value targets that will recover the most money or disrupt the largest criminal organizations. Ebola Relief Fraud As a country, we have become accustomed to reading stories about fraud in healthcare, financial services, and government programs. It doesn’t make it right, but it’s certainly not new. Now though, news comes from the American Red Cross that $5 million of Ebola relief funds were fraudulently disbursed on overpriced supplies, fake customs bills, and even non-existent aid workers. These scams will be familiar to regular readers of this blog as they are similar to scams run against domestic subsidy programs. But Ebola relief efforts?Between 2014 and 2016, Ebola raged through parts of Africa, claiming over 10,000 lives in Liberia, Sierra Leone, and Guinea. In response, the Red Cross collected and distributed over $100 million in aid, while doctors, nurses, and other volunteers risked their lives to save those suffering or at risk from the disease. Into this tragedy, naturally, came the fraudsters who recognized an ideal opportunity given the large amounts of aid money and the necessarily lax controls over disbursements.Now the Red Cross finds itself having to apologize to donors who realize that 5% of their contributions were stolen. While I don’t know all the details about the Red Cross’s financial controls, I can only imagine how difficult a task it was to make sure money was distributed quickly to only well-intentioned people and organizations.If anything, I believe this is one more reason for strong enforcement of criminal fraud after it has been committed. Trying to prevent fraud by adding bureaucracy and controls to the funds distribution process would likely add to delays during an emergency. Rigorous investigations and strong prosecutions, on the other hand, could act as a deterrent to future fraud. If not, at least it would prevent these fraudsters from plying their “trade” during other disasters. Comment (0) Comments are closed.