Americans are offered a range of government-funded benefit programs that promote citizen well-being. These programs are vital to the health and growth of our country and its people.
Yet the sheer size of these programs makes even a small percentage of fraud relatively significant. The need for federal agencies and state government to partner to address fraud and other improper payments is a rising issue — and technology, in the form of big data analytics, can help.
According to the Congressional Budget Office, government spending on means-tested programs and tax credits for financially qualified workers has increased tenfold over the past 40 years. In 2012, the federal government spent more than $400 billion on four of the largest programs: Medicaid ($251 billion); Supplemental Nutrition Assistance Program (SNAP) ($80 billion); the Earned Income Tax Credit ($54 billion); and Supplemental Security Income ($50 billion). These numbers climb higher when you consider that additional funds are often contributed by states as they pay half or supplement costs for these major programs.
If, for example, these four programs had a fraud rate of 1 percent, total fraudulent payments would be over $4 billion. News stories, though representative of a very small portion of the recipient population, create negative public perception and reduce support for programs that provide critical support to a vast majority of well-intentioned recipients.
A local newspaper in Kentucky reported the conviction of a woman who concealed her living arrangements to collect approximately $280,000 in fraudulent Supplemental Security Income and Medicaid benefits. Eleven Louisiana residents were convicted of fraudulently receiving more than $81,000 in SNAP and Child Care Assistance Program benefits after concealing information about their living arrangements and earnings.
While many of these programs are administered at the state level, federal agencies can go further to reduce negative public perception and keep both federal and state dollars supporting those who need it. States with greater means and focus on these issues can make a local impact, but a focused federal effort can help enable all states to make a significant impact in the national program.
Federal agencies, such as the Department of Health and Human Services, the IRS and the Social Security Administration can work with states to better use data and innovative analytics to more accurately predict recipients likely to commit fraud.
To truly understand fraud and emerging fraud trends, agencies need to understand their recipients’ behaviors. Not only should we base our fraud analytics on spending patterns, we must also look at demographic trends and interactions with spending. Once we understand our recipient population, we can help states focus on the data to educate business processes from client education, eligibility, fraud detection and prevention, as well as disposition. This provides an end-to-end solution that will enable these programs to operate the most efficiently.
This methodology will enable states that administer public assistance programs to focus on the health of the entire program and ensure we get these precious benefits to the people that need it. Some federal programs have begun to employ techniques today that are setting the foundation for a solid program that has integrity.
Public assistance programs provide an essential safety net for those in need. At a time when every government budget dollar is scrutinized, federal agencies and state governments must partner to ensure the highest standards of program integrity, spending money efficiently to catch bad actors and re-allocating cost savings to provide support to those who need it most.