Improving Unemployment Insurance Claim Fraud Detection

The Challenge

The Unemployment Insurance Integrity Center of Excellence, a collaborative hub for all Unemployment Insurance (UI) state agencies, funded the development of a Data Analytics and Predictive Modeling (DAPM) tool to support predictive analysis for Unemployment Insurance Integrity across 53 state and U.S. territory constituents. The goal for the development was to use data analytics to improve detection of fraud, overpayments, and underpayments in unemployment insurance. The solution needed to identify risky unemployment insurance claims, claimants, and employers while also helping states balance the competing requirements of promptness and accuracy of payments.

The Solution

Elder Research and our subcontractors developed an innovative, flexible, and robust predictive analytics tool that allows states to dig deeper into their data to uncover improper unemployment insurance payments. Three state workforce agencies with diverse characteristics (New York, Idaho, and Kansas) were selected to pilot the program. Elder Research worked with the client and subject matter experts from the pilot states to establish the business needs of each state’s UI program, uncover pain points and improvement opportunities, inventory relevant data sources, and identify all technical, legal, and regulatory constraints for the project.

Three machine learning algorithms were trained using state UI data to help identify improper payments and the outputs of several modules were fused to predict the likelihood that an individual would commit fraud based on his or her network of associates. High-risk claimants are generally tightly connected to known bad actors as shown in the example link graph below.

Figure 2 - Sample Link Graph-1

To access and analyze the claim risk scores and supporting data the pilot states used a robust BI tool developed by Elder Research called RADR (Risk Assessment Data Repository) — a custom solution that combines risk modeling with data visualization to prioritize caseloads, uncover new leads, and accelerate investigation.


The DAPM tool, highly acclaimed by the National Association of State Workforce Agencies (NASWA) and the New York Unemployment Insurance Center of Excellence, is scalable and deployable across all states and provides a framework that enables the Center and the states to deploy increasingly sophisticated UI program strategies over time. An estimated $972,000 in recoverable and $392,000 in non-recoverable overpayments savings were projected annually using this fraud detection tool. The automated scoring algorithms directly improved the speed, quality, and consistency of claim determinations and the plan is to implement the DAPM tool nationwide over the next few years.

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