US states will pay for food aid mistakes from next year, making data quality a budget issue
States with SNAP payment error rates above 6 per cent must start covering part of benefit costs. Fixing inconsistent records across agencies is the cheapest defence.
More than 40 million Americans rely on the Supplemental Nutrition Assistance Program (SNAP), and from next year the accuracy of states' data will carry a direct financial cost, according to an analysis in StateScoop.
Federal legislation ties states' funding obligations to their payment error rates. States that keep SNAP error rates below 6 per cent retain full federal funding; those above the threshold must begin covering part of benefit costs the federal government used to pay, an obligation that can run to hundreds of millions of dollars.
Where errors come from
Eligibility depends on income, citizenship, assets and household composition, information often pulled from different agencies with separate systems and data standards. The same Social Security number may be formatted differently from one system to another, and agencies may use different names for identical fields. That makes it hard to tell whether two records describe the same person, creates duplicates and forces staff to reconcile records by hand.
When verification stalls, families wait for help they need to buy food. Errors in the other direction, overpayments, now cost the state.
Make existing data work together
The analysis argues that modernising SNAP "is not about collecting more data, but about making the data states already have work better together". In practice that means common data standards across agencies, shared matching rules for identifying people and records that update once and flow to every programme that uses them.
The new funding rule turns a long-standing service problem into a budget one. For state technology leaders, it is an unusual opportunity: data quality work that rarely wins funding now has a measurable return.
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