Navigating the Complexity and Variability of Government Data to Improve Payment Integrity: Key Insights from an Expert Roundtable

Earlier this year, the IBM Center for The Business of Government and the National Academy of Public Administration brought together a diverse group of experts and stakeholders for a roundtable discussion –  "Recommendations for Improving Payment Integrity" – to discuss strategies for enhancing the integrity of government payments (see first overview post on how AI and emerging technologies can support such strategies).

This post—the second in a three-part series highlighting key insights, major themes and findings from the roundtable—focuses on using data proactively to identify potential issues before they occur: shifting from a reactive “pay and chase” approach to a preventative one. During a breakout session at the Roundtable entitled, “Complexity and Variability of Data,” participants discussed ways to improve data management, foster digital labor, address privacy concerns, and enhance public trust.

Data silos present a challenge. 

Breaking down data silos and developing use case scenarios are essential to addressing the variability and complexity of data. Currently, fragmented data across many financial systems hinders the development of comprehensive analysis to drive better decision-making and improve payment integrity. By identifying use cases that cross agency boundaries, government leaders can collaborate more effectively to build interoperable systems that enable sharing.

Data standards can help ease interagency information sharing. 

Data standards offer another way to help facilitate information sharing that can reduce fraud, waste, and abuse across agencies. Stakeholders stressed the importance of a unified approach to data management. Establishing data standards allows agencies to work together more seamlessly to streamline operations and improve overall service delivery. Standards can also help agencies connect the dots and focus on outcomes, rather than navigating inconsistent terminology.

Digital labor can fill workforce capacity gaps. 

Recent progress in the use of “digital labor” (such as bots to improve workflow) can be leveraged to help program and financial teams make faster and more accurate decisions. By identifying key areas where technology can augment human capabilities, government executives can optimize limited resources, improve efficiency, and drive innovation. This requires collaboration between IT and business leaders to determine where and how digital tools can be most effectively utilized.

Data should be made more transparent and user-friendly for the public. 

The session also underscored the importance of addressing the human element of data management. Historically, the focus has been on the data itself, without taking into consideration how people might interact with the data. By building transparent and usable systems that help educate citizens on data usage, and by providing easily accessible information, government agencies can bolster public support for payment integrity initiatives.

Public trust is paramount –  to earn it, agencies should prioritize transparency in how data is used, while implementing strong security and privacy safeguards. This means clearly communicating how government data on citizens is collectedand protected; ensuring timely and accurate information through interoperable systems; and sharing data in ways that deliver public value without compromising individual privacy or national security.

Next Steps

Several key challenges and potential solutions emerged as priorities for action, including:

• securing sufficient resources to implement consistent data standards,
• creating adaptable frameworks for navigating existing laws such as the Privacy Act and Paperwork Reduction Act,
• improving the reliability of data sets used in AI and decision-making systems,
• strengthening defenses against emerging threats like deepfakes and data breaches,
• addressing the lack of incentives that hinder inter-agency data sharing, and
• managing the organizational and cultural change required to adopt common systems.

When prioritizing these issues, participants emphasized the importance of tackling siloed systems, improving automated risk assessments, and establishing data fusion centers. In the near term, importance was placed on expanding data sharing efforts –  particularly across agencies and with the Treasury’s Bureau of the Fiscal Service, and  through initiatives like the Do Not Pay program.

The final post in this series will explore how improving citizen experience can help accelerate the delivery of accurate benefits to the public who depends on government services.