Today’s hearing is about how the government can use data and information technology to better prevent fraud and abuse, increase the efficiency of benefit programs, and produce savings for U.S. taxpayers.

That’s an ambitious set of goals.   

We will start by asking about how current efforts to use data and technology are working to improve program administration and benefit accuracy.  Then we will expand on that by asking public and private experts how we can use data to provide better services for benefit recipients and at lower costs to taxpayers.

One key goal involves preventing improper payments.  As this chart shows, we have a lot of work to do.  In 2010 total improper payments by just the Federal government reached a staggering $125 billion.  That reflects payments that went to the wrong recipient, in the wrong amount, or that were used in a fraudulent manner.  I am alarmed to note that $125 billion in improper payments is an average of over $1,000 per household in the United States! 

Two of this Subcommittee’s programs, Unemployment Insurance and Supplemental Security Income, accounted for almost one-fifth of those improper payments, costing taxpayers over $23 billion last year.  

To address those types of errors and improve administrative efficiency, government needs to work a lot smarter.  So we have asked lots of smart people here today to help us learn about the current state of data matching and its potential for making major strides in program efficiency and effectiveness in the future. For example, 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.  We want to apply those same sorts of lessons in our programs as well.

We have seen some of those lessons already applied in States like Utah and Florida. They are using data matches to fill application forms with reliable and verified data, reducing the manual burden on caseworkers and increasing payment timeliness and accuracy. This also allows caseworkers more time to spend with beneficiaries handling more complex cases, as they should.

On the Federal level, a data match success story involves legislation crafted by this subcommittee related to prisoners who should not be collecting disability checks.  As a result of that legislation, the Social Security Administration now has a system by which they collect timely prisoner data from State and local jails, rather than relying on the honesty of inmates – literally – to end their own benefits.  From 1997-2009 this system helped identify over 720,000 incarcerated individuals who should not have been receiving SSI benefits, contributing to billions of dollars in savings each year. It’s been so successful that this data is now shared with the child support enforcement and food stamps programs. 

Looking forward, we are interested in promoting the development of a more common set of data elements across programs. This will improve efficiency and savings in our programs as well as other costly benefit programs like food stamps and Medicaid that many of our programs’ recipients also collect.  These issues stretch beyond our Subcommittee’s borders to include laws like the Computer Matching and Privacy Protection Act of 1988.  That means we will have to work with other Committees to achieve real changes, like making updates for current technology and allowing for computer matching agreements to be completed in a more timely manner. 

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.  Those are goals we should all agree on. 

We look forward to all of our witnesses’ testimony. 

###