“We’ve seen the private sector find ways to use data to more efficiently detect patterns of misuse, such as when credit cards are lost or stolen, and streamline backend payment processing,” Davis, the subcommittee’s chairman, said in his prepared remarks. “We want to apply those same sorts of lessons in our programs as well.”
For his part, Rep. Lloyd Doggett, the subcommittee’s ranking member, agreed that the government should strive to tamp down abuse and waste. But he also said that data matching could help ensure that the government finds those who need help.
“Just as data sharing can detect individuals who should not receive benefits, it also can be used to improve outreach to Americans who are eligible for assistance, but who are not receiving it,” the Texas Democrat said in his prepared statement.
Data matching, in short, means confirming information after looking at multiple databases.
At Friday’s hearing – which featured both public- and private-sector representatives – Davis said data matching could help roll back the $23 billion in improper payments for unemployment insurance and Supplemental Security Income that taxpayers had to foot last year.
“Ultimately, improving data matching will help us better measure the effectiveness of multiple programs and more efficiently target resources to achieve goals like promoting more work and earnings, reducing poverty, and ending dependence on government benefits,” he said.
But Doggett also asserted that House Republicans were trying to cut spending this year for other initiatives that look to rein in fraud and abuse.