From Detection to Prevention: AI for Government Fraud, Waste and Abuse​

Fraud, waste, and abuse (FWA) remain a major global challenge for public sector organisations, with estimates suggesting up to 16% of government budgets may be lost to fraud, waste, and abuse. At the same time, fraud is becoming increasingly sophisticated, with 95% of government fraud professionals reporting AI-enabled fraud schemes and 70% experiencing an increase in these threats overthe past five years.​

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Despite significant investment in controls and audit mechanisms, many agencies still struggle to detect and prevent FWA effectively. Fragmented data systems, legacy infrastructure, and siloed operations continue to limit visibility across programmes anddepartments. Traditional rule based and manual approaches also struggle to keep pace with evolving fraud tactics, resulting in delayed detection and financial leakage that is often difficult to recover. Only 1 in 10 public sector organisations believe they currently have the tools and resources needed to effectively combat fraud, highlighting a clear capability gap.​

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This webinar will explore how data, artificial intelligence, and advanced analytics are transforming the public sector’s ability to combat FWA. It will highlight practical applications such as predictive detection, anomaly identification, and network analytics, alongside the importance of strong data foundations, governance, and ethical considerations. Participants will gain insight into how governments can move from reactive investigations to proactive prevention, strengthening operational efficiency, protecting public funds, and enhancing citizen trust.​

 

Key Takeaways:

• Demonstrate how modern data capabilities and AI-driven approaches enable governments to shift from reactive fraud detection to proactive, intelligence-led prevention and more effective response to evolving FWA risks.​

• Raise awareness among public sector leaders of the increasing complexity of external and internal fraud challenges, including fragmented data systems, legacy infrastructure, and rapidly evolving fraud tactics that require new analytical approaches.​

• Engage government agencies and decision-makers exploring modern fraud detection and investigation capabilities, while highlighting practical use cases and real-world applications of AI in improving integrity, efficiency, and trust in public services.​