Charles Lyons-Burt
By Christina Seiden, senior vice president of strategic growth at Excella
With billions in taxpayer dollars at stake, agencies can’t continue using methods that catch fraud only after the damage is done. However, federal agencies face a significant challenge. Manual oversight, coupled with aging IT infrastructure, simply can’t keep up with massive volumes of data and increasingly complex fraud strategies. When federal employees spend weeks reviewing documents that modern technology could process in hours, agencies are missing opportunities to maximize taxpayer resources.
AI: Enhancing Human Expertise, Not Replacing It
The solution isn’t to replace human expertise—it’s to enhance it using artificial intelligence. AI transforms fraud detection from reactive to proactive, amplifying human judgment and boosting efficiency.
The results are impressive. When the U.S. Department of Health and Human Services’ Office of the Inspector General implemented an AI-powered fraud detection system, they saved over 4,000 work hours annually through automated audit analysis and were empowered to review 900,000 contracts and grants more efficiently. The real value? These systems make human judgment more powerful by directing investigators to high-risk behaviors in grant recipients that require the most attention.
At Excella, we believe efficiency isn’t about reducing staff—it’s about empowering each person to handle cases more effectively.
Key Components of an AI Solution
Through our work at agencies like HHS OIG and U.S. Citizenship and Immigration Services, we at Excella have identified five key components for modern and effective fraud prevention systems:
1. Smart Automation and Advanced Analytics
AI solutions should utilize a combination of natural language processing and deep neural networks to find patterns in existing data that humans may miss. Document processing can be further automated with topic modeling and risk scoring to classify and prioritize cases for faster review.
At HHS OIG, these capabilities have processed over half a million audits—transforming what was once considered impossible with manual methods into an automated process with consistent results.
2. Unified Data Architecture
AI is only as good as the data it’s fed. Implanting AI requires a clean-up and standardization of data which can be challenging given that fraud patterns often span multiple systems. To build a solid data foundation, AI implementations should:
- Consolidate data pipelines linking disparate systems
- Automate routine data refreshes to eliminate manual collection
- Ensure data integrity with quality monitoring systems
- Utilize scalable cloud architecture to process millions of records securely
At USCIS, this approach condensed 500 million identity records into 90 million unique identities, giving investigators a comprehensive picture previously unavailable. This unified view reveals connections that would otherwise remain hidden in siloed systems.
3. Proactive Anomaly Detection
Detecting fraud after the fact is valuable but still means the agency is incurring high costs to recover assets. AI can help shift from a reactive to a proactive approach by speeding the detection of suspicious patterns from weeks to hours. This is accomplished with text analytics spotting connections across large document sets. Once detected, AI-powered workflows can post real time alerts to people who can act on suspicious activity.
Agencies can identify potential fraud before improper payments are made. Grant managers can spot high-risk recipients before awarding additional funding and immigration services can detect fraud patterns across thousands of applications in hours instead of weeks.
4. Intuitive Visual Analytics
Making data actionable for investigators means converting complex information into a consumable format. Interactive dashboards can show fraud patterns by region and time and provide advance filtering options to narrow focus and explore additional connections.
What once required analyzing dozens of separate reports now happens in a single integrated view, dramatically accelerating the investigation process. Investigators can identify anomalies and focus on promising leads in minutes rather than days.
5. Human-Centered Implementation
Technology only delivers value when people use it. Successful implementations include user-friendly design that evolves with feedback. Ongoing training should include:
- Role-based training tailored to specific job needs
- Communities of practice for knowledge sharing
- Train-the-trainer programs to build internal expertise
At HHS OIG, this human-centered approach resulted in an AI solution that now serves over half the organization’s user base. Instead of technology gathering dust, it’s becoming an essential part of how agencies operate.
AI and Human Expertise—The Winning Combination for Fraud Prevention
Federal agencies implementing solutions with these components see dramatic reductions in processing time, saving thousands of staff hours yearly. Investigation workflows become more efficient, with queries returning results in seconds rather than hours.
As government agencies continue modernizing their fraud prevention efforts, AI capabilities will evolve with more sophisticated pattern recognition and improved interagency coordination. However, the core principle remains constant: effective fraud prevention works best when human expertise partners with technology. The most successful agencies will be those that see AI not as a replacement for human judgment, but as a force multiplier that helps their teams accomplish more with less effort.
