Supplemental Nutrition Assistance Program: Enhanced Detection Tools and Reporting to Combat Recipient Fraud Are in Development
Released: 2016-06-09T00:00:00

Letter

Background

The goal of SNAP, formerly known as the federal Food Stamp Program, is to help low-income individuals and households obtain a more nutritious diet and help alleviate their hunger. It does so by supplementing their income with benefits to purchase allowable food items. The federal government pays the full cost of the benefits and shares the responsibility and costs of administering the program with the states. Specifically, FNS is responsible for promulgating program regulations and ensuring that states comply with these regulations by issuing guidance and monitoring their state activity. FNS headquarters officials are assisted in this oversight work by federal officials in seven regional offices. FNS also determines which retailers are eligible to accept SNAP benefits in exchange for food and investigates and resolves cases of retailer fraud. State officials, on the other hand, are responsible for determining the eligibility of individuals and households, calculating the amount of their monthly benefits and issuing such benefits on an electronic benefit transfer (EBT) card in accordance with program rules. States are also responsible for investigating possible violations by benefit recipients and pursuing and acting on those violations that are deemed intentional.

Trafficking is an intentional program violation that includes acts of fraud, such as making false or misleading statements in order to obtain benefits and trafficking (i.e., using benefits in unallowable ways, such as by exchanging benefits for cash or non-food goods and services or attempting to do so). For example, recipients can traffic benefits by selling EBT cards to another person, exchanging the EBT card and the corresponding Personal Identification Number (PIN) for cash or non-food goods or services (e.g., rent or transportation). These sales can occur in person or by posting offers on social media and e-commerce sites. Recipients can then contact state agencies to report the sold EBT cards as lost or stolen and receive new cards which can be used for future trafficking transactions, for example, when the benefits are replenished the next month.

According to a September 2012 U.S. Department of Agriculture Office of Inspector General (USDA OIG) report, the magnitude of program abuse due to recipient fraud is unknown because states do not have uniform ways of compiling the data that would provide such information. As a result, the USDA OIG recommended that FNS determine the feasibility of creating a uniform methodology for states to calculate their recipient fraud rate. FNS reported that it took action on this recommendation but ultimately determined that it would be infeasible to implement as it would require legislative authority mandating significant state investment of time and resources in investigating, prosecuting and reporting fraud beyond current requirements.

Selected States Faced Challenges in Detecting Benefit Fraud, and FNS Lacked Reliable Data about State Efforts

To Detect Fraud, Selected States Employed Tools Such As Data Matching, Referrals, Analysis of Transaction Data, and Website Monitoring

In the selected states we reviewed in 2014, officials told us they were using well-known tools for detecting potential recipient eligibility fraud, such as data matching and referrals obtained through fraud reporting hotlines and websites. Specifically, at that time, all 11 states that we reviewed had fraud hotlines or websites, and all matched information about SNAP applicants and recipients against various data sources to detect those potentially improperly receiving benefits, as FNS recommended or required. (See table 1.)

Beyond the required and recommended data matches, at the time of our report, Florida, Texas, Michigan, and one county in North Carolina used specialized searches that checked numerous public and private data sources, including school enrollment, vehicle registration, vital statistics, and credit reports to detect potential fraud prior to providing benefits to potential recipients. Florida officials we interviewed shifted the majority of their anti-fraud resources to more cost-effective and preventive efforts in identifying potential fraud by developing tools geared towards detecting eligibility fraud and improper benefit receipt, such as identification verification software and profiles that case workers could use to identify error-prone applications. These state officials stated that this focus on preventive efforts was key to helping them manage recent constraints on their investigative budgets.

To track potential trafficking, officials in the 11 states reported that they analyzed patterns of EBT transactions and monitored replacement card data and online postings pursuant to FNS’s requirements and guidance. (See table 2.)

In 2014, Most Selected States Reported that Their Investigations’ Effectiveness was Hindered by Limited Staffing and Caseload Increases, but Some Leveraged Additional Resources

At the time of our 2014 report, most of the selected states reported difficulties in conducting fraud investigations due to either reduced or stagnant staff levels while SNAP recipient numbers greatly increased from fiscal year 2009 through 2013. (See figure 1.) Furthermore, state investigators in all 11 states we reviewed were also responsible for pursuing fraud in other public assistance programs, such as Medicaid, Temporary Assistance for Needy Families and child care and housing assistance programs.

However, at the time of our report, some states implemented a strategy to leverage their available investigative resources. Specifically, four of the states we reviewed—Florida, Massachusetts, Michigan and Nebraska— had implemented and two states—Maine and North Carolina—were in the process of implementing state law enforcement bureau (SLEB) agreements. According to FNS officials, the agency was supportive of states’ efforts to establish these agreements between state SNAP agencies and federal, state, and local law enforcement agencies, which would enable state SNAP investigators to cooperate in various ways with local, state, and federal law enforcement agents, including those within the USDA OIG. For example, under these agreements, law enforcement agencies can notify the SNAP fraud unit when they arrest someone who possesses multiple EBT cards, and SNAP agencies can provide “dummy” EBT cards for state and local officers to use in undercover trafficking investigations. Officials in one county in Florida told us at the time of our report that this type of cooperation allowed local police officers to make 100 arrests in its first undercover operation of recipients who were allegedly trafficking SNAP benefits.

At the time of our report, some state officials suggested changing the financial incentives structure to help support the costs of investigating potential SNAP fraud because some investigative agencies were not rewarded for cost-effective, anti-fraud efforts that could prevent ineligible people from receiving benefits. According to GAO’s Fraud Prevention Framework, investigations, although costly and resource-intensive, can help deter future fraud and ultimately save money. Officials in one state told us that it would help its anti-fraud efforts if FNS would provide additional financial incentives for states to prevent potential fraud at the time of application beyond what is currently provided for recovered funds. Specifically, when fraud by a recipient is discovered, the state may generally retain 35 percent of the recovered overpayment, but when a state detects potential fraud by an applicant and denies the application, there are no payments to recover.

In 2014, Selected States Reported Limited Effectiveness in Using Automated Monitoring Tools for Detecting Online Fraud and Replacement Card Data as a Detection Tool

In our 2014 report, we found that, upon testing, FNS’s recommended approaches to detecting online fraud were of limited utility and selected states had limited success with using FNS’s required approach to replacement card monitoring. Specifically, we found that FNS provided states with guidance on installing free web-based software tools for monitoring certain e-commerce and social media websites for online sales of SNAP benefits, but some officials from the selected states reported problems with these detection tools. According to FNS, these tools could automate the searches that states would normally have to perform manually on these websites, which states reported as being cumbersome and difficult given limited resources. Of the 11 states we reviewed, officials from only one reported that the tool worked well for identifying SNAP recipients attempting to sell their SNAP benefits online. At the time of our review, FNS officials acknowledged that there were limitations to the monitoring tools, and stated that they provided these tools at the request of states to help with monitoring efforts.

In 2014, we tested these automated detection tools for certain periods of time on selected geographical locations covering our selected states and found them to be of limited effectiveness for states’ fraud detection efforts. For example, our testing of the recommended automated tool for monitoring e-commerce websites found that the tool did not detect most of the postings found through our manual website searches. Specifically, out of 1,180 postings we reviewed manually, we detected 28 postings indicative of potential SNAP trafficking. Twenty-one of these 28 postings were not detected by FNS’s recommended monitoring tool. We also found the automated tool for monitoring social media websites to be impractical for states’ fraud detection efforts, given that, for example, it could not be tailored to a specific location. We concluded that this could have potentially limited a state’s ability to effectively determine whether the postings detected were relevant to the state’s jurisdiction.

In 2014, we also reported that FNS required that states examine replacement card data as a potential indicator of trafficking, but state officials we interviewed reported difficulties using the data as a fraud detection tool. In 2014, FNS finalized a rule requiring states to monitor replacement card data and send notices to those SNAP households requesting excessive replacement cards, defined as at least four cards in a 12-month period. Officials we interviewed in the 11 states reviewed reported tracking recipients who make excessive requests for replacement EBT cards, as required by FNS, but said they had not had much success in detecting fraud through that method. Specifically, officials in 4 states reported that they had not initiated any trafficking investigations as a result of the monitoring, officials in 5 states reported low success rates for such investigations, and officials in 1 state reported that they had just started tracking the data. Officials in only 1 state reported some success using the data to detect potential trafficking. Furthermore, officials from 7 of the 11 states we reviewed reported that the current detection approach specified by FNS often led them to people who had made legitimate requests for replacement cards for reasons such as unstable living situations or a misunderstanding of how to use the SNAP EBT card. At the time of our report, FNS was aware of states’ concerns about the effectiveness of this effort, but continued to stress that monitoring these data was worthwhile.

Targeted Analysis of Excessive Replacement Cards Found Potential Recipient Trafficking

We found that while all of the selected states reported analyzing SNAP replacement card data to detect fraud as required by FNS, a more targeted approach to analyzing high-risk replacement card data potentially offered states a way to better use the data as a fraud detection tool. Specifically, we analyzed fiscal year 2012 replacement card data in three selected states—Michigan, Massachusetts, and Nebraska—using an approach aimed at better identifying SNAP households requesting replacement cards that are at higher risk of trafficking benefits. Our approach took into account FNS’s regulation that defined excessive replacement cards as at least four requested in a 12-month period. However, we also considered the monthly benefit period of replacement card requests by focusing on SNAP households receiving replacement cards in four or more unique monthly benefit periods in a year. Based on our analysis, we determined that because SNAP benefits are allotted on a monthly basis, a recipient who is selling the benefits on their EBT card and then requesting a replacement card would generally have only one opportunity per month to do so. Thus, if a SNAP recipient was requesting a replacement card because they had just sold their EBT card and its associated SNAP benefits, it was unlikely that there would be more benefits to sell until the next benefit period. As a result, we determined that additional replacement card requests in the same benefit period may not indicate increased risk of trafficking.

Using this approach in the three selected states, our 2014 analysis reduced the number of households that should be considered for further review compared to the FNS requirement that states look at replacement cards replaced four or more times in 12 months. We then reviewed fiscal year 2012 transaction data for this smaller number of households to identify suspicious activity that could indicate trafficking. We identified 7,537 SNAP recipient households in these three selected states that both received replacement cards in four or more monthly benefit periods in fiscal year 2012, and made at least one transaction considered to be a potential sign of trafficking around the time of the replacement card issuance, as shown in the table below. We found that these 7,537 households made over $26 million in total purchases with SNAP benefits during fiscal year 2012. (see table 3.)

We also found that by comparing the number of benefit periods with replacement cards and the total number of transactions flagged for potential trafficking, states may be able to better identify those households that may be at higher risk of trafficking. For example, as shown in the figure below, while there were 4,935 SNAP households in Michigan that received an excessive number of replacement cards, we identified just 39 households that received excessive replacement cards and made transactions resulting in 10 or more trafficking flags. We concluded in 2014 that while state SNAP officials may not want to limit their investigations to such a small number of households, this type of analysis may help provide a starting point for identifying higher priority households for further review. Furthermore, we reported that our more targeted approach may also be particularly helpful given that states had limited resources for conducting investigations.

In 2014, We Reported that FNS Had Increased Its Oversight of State Anti- Fraud Activities but Lacked Reliable Data on These Efforts

In 2014, we reported that FNS had increased its oversight of state anti- fraud activities in recent years by issuing new regulations and guidance, conducting state audits, and commissioning studies on recipient fraud since fiscal year 2011. For example, in fiscal year 2013, for the first time, FNS examined states’ compliance with federal requirements governing SNAP anti-fraud activities through Recipient Integrity Reviews. These assessments included interviews with state officials, observations of state hearing proceedings, and case file reviews in all 50 states and the District of Columbia. Following these reviews, FNS regional officials issued state reports that included findings and, where appropriate, required corrective actions.

Despite these efforts, at the time of our report, FNS did not have consistent and reliable data on states’ anti-fraud activities because its reporting guidance lacked specificity. For example, through our review of the 2013 Recipient Integrity Review reports, we also found that FNS had a nationwide problem with receiving inaccurate data on state anti-fraud activities through the Program and Budget Summary Statement (Form FNS-366B). Some federal and state officials we interviewed recognized that there was not a consistent understanding of what should be reported on the FNS-366B form because the guidance from FNS was unclear. For example, on the form in place during the time of our report, FNS instructed states to report investigations for any case in which there was suspicion of an intentional program violation before and after eligibility determination. According to state and federal officials we interviewed, this information did not clearly establish a definition for what action constitutes an investigation and should then be reported on this form.

After reviewing states’ reports, we found examples of inconsistencies in what states reported as investigations on the FNS-366B forms. Specifically, in fiscal year 2009, one state had about 40,000 recipient households, but reported about 50,000 investigations. During the same year, another state that provided benefits to a significantly larger population (about 1 million recipient households) reported about 43,000 investigations. Officials from the state that served the smaller population, but had the larger number of investigations, explained that they included investigative activities such as manually reviewing paper files provided by the state’s Department of Labor for each SNAP recipient with reported wages in the state. Officials from the state that served the larger population said that they counted the number of times a potential fraud case was actively reviewed by investigators, including interviews with witnesses and researching of related client information. Given these differences, state officials said that FNS and states were not able to compare program integrity performance because there was no standardization of data collection across states.

FNS Is Working to Address GAO Recommendations to Enhance Detection Tools and Reporting

As a result of our 2014 findings, we made several recommendations, and FNS officials agreed with all of these recommendations and are taking actions to address them. Specifically, we recommended that the Secretary of Agriculture direct the Administrator of FNS to: explore ways that federal financial incentives can better support cost- effective state anti-fraud activities; establish additional guidance to help states analyze SNAP transaction data to better identify SNAP recipient households receiving replacement cards that are potentially engaging in trafficking, and assess whether the use of replacement card benefit periods may better focus this analysis on high-risk households potentially engaged in trafficking; reassess the effectiveness of the current guidance and tools recommended to states for monitoring e-commerce and social media websites, and use this information to enhance the effectiveness of the current guidance and tools; and take steps, such as guidance and training, to enhance the consistency of what states report on their anti-fraud activities.

While FNS agreed with the recommendations and is taking steps to address them, it has yet to fully develop the detection tools and improved reporting methods that would address these recommendations.

To explore ways to provide better federal financial incentives, FNS reported it published a Request for Information in the Federal Register in 2014 to solicit state and other stakeholder input on how it could more effectively incentivize states to improve overall performance, including in the area of program integrity, with new bonus awards. However, more recently, FNS officials reported that, based on the feedback from this process, they have decided not to pursue bonus awards for anti-fraud and program integrity activities at this time. At the time of our 2014 report, FNS officials also stated they could not make changes in the state retention rate for overpayments without a change to federal law.

FNS officials reported that they have provided states with technical assistance for how to effectively utilize replacement card data as a potential indicator of trafficking. Specifically, FNS has worked with seven SNAP state agencies: New York (Onondaga County), Pennsylvania, South Carolina, Wisconsin (Milwaukee County), California (Los Angeles County), Kansas, and Texas to help these states more effectively identify SNAP recipient trafficking, using models that incorporate predictive analytics. FNS officials stated that the models use a variety of eligibility and transaction data, including replacement card data, and have demonstrated a significant improvement in effectiveness in these states. According to FNS officials, over 90 percent of South Carolina’s investigations of potential trafficking resulted in disqualifications from SNAP, which FNS officials stated is an increase of 29 percent from the state’s investigation success rate prior to using FNS’s model. Based on these state results, FNS officials stated that FNS was targeting four additional states in fiscal year 2016 for technical assistance in implementing the model: Arizona, the District of Columbia, Utah, and Washington. Furthermore, as of May 2016, FNS officials had reported that FNS is conducting a training program for state technical staff to teach them how to build predictive models that incorporate the use of card replacement data.

FNS officials also reported that they continue to provide technical assistance to states on the effective use of social media and e-commerce monitoring and have further studied the use of these tools. Most recently, FNS officials reported that, in 2016, the agency conducted an analysis to evaluate states’ current use of social media in their detection of SNAP trafficking. Based on the information gained through this analysis, FNS officials reported that they plan to determine how best to present further guidance to state agencies on using social media to combat trafficking.

As of May 2016, FNS had also redesigned the form FNS-366B used to collect consistent recipient integrity performance information and submitted a draft to the Office of Management and Budget (OMB). FNS officials anticipate OMB approval of the revised form prior to the end of fiscal year 2016, and the form is expected to be implemented in fiscal year 2017. FNS reported it published an interim final rule on January 26, 2016, (effective March 28, 2016), changing the reporting frequency of the form from an annual submission based on the state fiscal year to a quarterly submission based on the federal fiscal year. To date, FNS officials reported that they provided 4 separate trainings to approximately 400 state agency and FNS regional office personnel, covering the new and modified elements of the final draft form and the corresponding instructions. - - - - - In conclusion, the challenges that states have faced in financing and managing recipient anti-fraud efforts heighten the need for more efficient and effective tools for safeguarding SNAP funds. In order to provide useful guidance to best guide states in these efforts, FNS officials need reliable information on what can currently be done with available federal and state resources. As of May 2016, FNS officials have reported progress in studying current anti-fraud approaches and developing better data on them but are still in the process of developing the final tools and guidance for enhancing the integrity of the SNAP program.

Chairmen Meadows and Lummis, Ranking Members Connolly and Lawrence, and Members of the Subcommittees, this completes my prepared statement. I would be pleased to respond to any questions you may have at this time.

GAO Contact and Staff Acknowledgments

If you or your staff have any questions about this statement, please contact Kay Brown, Director, Education, Workforce, and Income Security Issues, at 202-512-7215. Contact points for our Offices of Congressional Relations and Public Affairs may be found on the last page of this statement. GAO staff who made key contributions to this statement include James Bennett, Kate Blumenreich, Alexander Galuten, Danielle Giese, Scott Hiromoto, Kathryn Larin, Flavio Martinez, Jessica Orr, Deborah Signer, Almeta Spencer and Shana Wallace.

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