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How Anomaly Detection Can Combat Government Waste, Fraud, and Abuse

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A recent report from the Government Accountability Office (GAO) found that  almost $1.4 billion in COVID-19 stimulus checks  were sent to deceased individuals. The fraud amounted to over one million erroneous payments. The data required to avert this loss of tax-payer money was readily available in government systems, but the data wasn’t accessible to the agency that needed it.  On its face, this sounds like a data-sharing problem. But even if the Social Security Administration (SSA) death index had been shared with the Department of Treasury (the agency that issued the stimulus checks), it wouldn’t have been enough. Why? Because there are 89 million records in the death index, and there are 143 million tax-payers in the United States. Detecting fraudulent applications amidst this volume of data cannot be done by employees alone. It requires data integration and software that looks for anomalies and alerts the employees before the checks go out.   There are many recent examples of this

Using Predictive Analytics to Model Incident Response Tabletop Exercises

  The key to a compelling incident response  tabletop exercise  involves modeling likely scenarios and demonstrating probable outcomes resulting from decisions made by the participants. Whether it be a cyberattack, a natural disaster, civil unrest, or all of the above simultaneously, government leaders need a platform with which to test their emergency response plans, challenge their business continuity assumptions, and assess their staff’s operational knowledge under pressure.  By exercising at regular intervals, government agencies can see in real-time where they can gain efficiencies and what gaps exist that need to be filled. Publishing the exercise results and sharing them across disciplines can be the catalyst for fixing broken processes and policies. Modern  business intelligence  (BI) tools and  predictive analytics  capabilities can significantly speed the time to value of these tabletop exercises by automating the decision tree and providing an instant feedback loop.  Because

Modeling and Simulation of Incident Management for Homeland Security

The Federal Emergency Management Agency (FEMA) established its  National Incident Management System (NIMS)  in 2004. A response to one of President George W. Bush’s Homeland Security Presidential Directives, NIMS sets guidelines for public and private sector collaboration in preventing, mitigating, and responding to domestic incidents.  Because NIMS “applies to all incidents, regardless of cause, size, location, or complexity,” modeling and simulation are vital to strengthening incident management tools. To manage incidents—a process that involves careful analysis and strategy—FEMA utilizes NIMS and the National Response Framework (NRF) to serve as the backbone of its methodologies.  Since 2004, a lot of work has gone into creating realistic scenarios that train government employees and private sector participants to act during an actual emergency. However, simulation scenarios are still largely executed manually with participants working at actual tabletops with notebooks and pap