The U.S. Department of Health and Human Services, Office of Inspector General (HHS OIG) wanted to bring several grants data sets together and leverage artificial intelligence (AI) to combat fraud, waste, and abuse by bringing the most useful data forward. HHS OIG had to overcome multiple challenges to introduce more automation and AI to support fraud analytics, including:
- Grant fraud
- Grantee funds mismanagement
- Data acquisition and access
- Large volume of data
- Inconsistent data interpretation
- & much more
To solve the challenges that HHS OIG was experiencing, Excella proposed an innovative analytics tool to modernize how people, process, and technology support results-oriented accountability for grants. The Grants Analytics Portal (GAP) solution was built in close collaboration with the OIG to provide faster and easier access to key data.
Using an AI model to seek key information in the text of the audit results and recognize patterns that are irregular can help to tailor results that are presented to users in the most useful way, saving auditor time and ultimately agency money. Instead of only having a large list of grantees and their associated audit reports, an OIG staff member can see a list of the grants with a likelihood of fraud alongside how many indicators of fraudulent or risky behaviors the audits discovered. The centralization of grants data and the identification of key data and patterns using machine learning models have revolutionized how auditors and investigators serve in the OIG.
Read our case study to learn how the use of artificial intelligence (AI) and machine learning in the GAP:
- Radically changed the ability of HHS OIG to oversee grant monies given to external third parties
- Equipped 1,600 HHS OIG employees with additional tools to reduce fraud, waste, and abuse in the HHS system
- Transformed the grant oversight structure, combining information about the grantee from several disparate government databases into a singular, detailed grantee profile
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