Stopping Fraud and Improper Payments

The Government Accountability Office (GAO) reported in March 2025 that the U.S. government loses somewhere between $233 billion and $521 billion annually to fraud, based on data from fiscal years 2018 through 2022. On top of that, improper payments by the government have totaled an estimated $2.8 trillion since fiscal year 2003.

The biggest difference between fraud and improper payment is intent – fraud is intentional deception, such as filing fake claims, while improper payments are mistakes such as overpayments or duplicate payments. Together they represent a massive loss of taxpayer monies.

Fraud analysis and improper payment detection use data analytics, AI, and rule-based systems to identify suspicious transactions, behaviors, or claims that deviate from normal patterns, preventing financial loss by catching deliberate fraud (like stolen cards) and accidental errors (like overpayments) through methods like pattern recognition, behavioral biometrics, and strong internal controls, balancing security with customer experience.

Learning Objectives:

• Identify the magnitude of fraud and improper payment in your agency through the use of data analytics
• Delineate steps to implement methods such as pattern recognition to detect anomalous behaviors
• Outline metrics to measure the positive impact of steps that prevent improper payments and identify instances of fraud