States Need Paradigm Shift to Weather New Federal SNAP Policies

The One Big Beautiful Bill Act will increase state share costs to administer the Supplemental Nutrition Assistance Program (SNAP). States are facing an average of $192 million annual increase in the state share to fund benefits issued to SNAP recipients. For some states, the potential liability exceeds $1billion annually. With so much state funding at risk as soon as 2027, states need to rethink their approach to SNAP payment accuracy and quality assurance to include advanced analytics.

One Big Dose of Tough Love

If states cannot lower their SNAP quality control payment error rates to under 6%, they face graduated increases in their annual state share liability. State share increases range from 5% to 15% of the total cost of annual SNAP benefits issued. States below the 6% threshold do not have to contribute a state share, and the cost is fully funded by the federal government.

While these state share percentages may seem small, they represent a significant fiscal challenge for states. This could mean over $1billion for California and New York. Yet, smaller states with higher error rates over 10% would face a 15% state share increase which could represent between $100 and $500 million annually. That is a bitter pill nearly all states will struggle to swallow without budget cuts elsewhere if these errors persist.

Why Are States Struggling with SNAP Payment Accuracy

Errors in SNAP eligibility determinations have always existed, and they may occur for many reasons. State eligibility systems may be quite old and use legacy technology making it difficult to adjust to policy changes or incorporate advancing technology. Newer eligibility systems often integrate multiple programs such as cash assistance (Temporary Assistance to Needy Families), food assistance (SNAP), and healthcare assistance (Medicaid) making them more complex and potentially prone to errors during and immediately after implementation. In my discussion with states, many report that more seasoned staff have retired, especially during COVID, and new staff tend to stay in eligibility determination for less than five years. It takes time to learn SNAP policy, how to use the eligibility determination system, and how to maintain efficient work processes. Thus, payment errors persist.

State SNAP Quality Assurance Approach is Outdated

Most states use statistical sampling to monitor SNAP error rate trends, not find and fix eligibility case errors. This is much like how the federal quality control payment error is determined. The problem is this approach measures an error rate by sampling a small number of cases relative to the total number of active SNAP cases.

This means while a state quality assurance team may estimate their error rate at 8%, they cannot tell you which of their active cases make up that percentage. Thus, they cannot find and fix those cases to effectively reduce their federal error rate. If this approach were truly effective, then 42 of the 50 states would not currently be subject to the One Big Dose of Tough Love and state share liabilities for their programs. They would already be under the 6% threshold.

Time to Change the Game

Just as Congress changed the rules with new legislation, states need to change their game in controlling SNAP payment errors. There is no time to hire and train hundreds of new quality assurance staff, and more seasoned staff would likely become checkers rather than performing daily eligibility determinations. Most eligibility determination systems lack the flexibility to institute technology changes in time to avoid the 2027 increased state shares.

However, SAS created a predictive model released earlier this year to help states find SNAP cases at higher risk for payment errors. This solution reviews all active cases to create a continuous monitoring system without adding additional quality assurance staff. The solution provides states with risk-scored results to help them focus their quality reviews more effectively. By finding and fixing case errors faster, states can lower their SNAP payment error rates and avoid paying increased state share costs of benefits. Even a reduction in SNAP error rates that lowers the state share costs would represent millions of dollars in cost savings for states.