Sagitec alerted the Maryland Department of Labor (MDOL) of potential fraud activity after identifying a spike in out-of-state Unemployment Insurance (UI) claims including regular and pandemic claims.
Sagitec performed an in-depth analysis of the claim activity in Maryland and quickly determined that a massive fraud scheme was attempting to defraud Maryland by utilizing automated bots and humans to file fraudulent claims. Sagitec consulted with MDOL and immediately froze most out-of-state accounts. Sagitec worked with MDOL and their banking vendor to block payments before they were made and where payments had been made block the use of those debit cards to more than 47,500 bogus claims saving Maryland and the Federal Department of Labor more than $501 million.
During the in-depth analysis, Sagitec was able to identify similar fraudulent activity in Maryland’s in-state claims. Details of the scheme have been shared with MDOL, the National Association of State Workforce Agencies (NASWA), and federal authorities for the benefit of all state workforce agencies (SWA).
With advances in predictive analytics, machine learning, and data modeling, there are technology solutions that can sift through historical claim data on previous fraud cases and produce a trained fraud model that can accurately predict the likelihood that claimants will commit fraud. These models can be applied to UI claim data to identify fraud before it occurs or very early in the process so follow up and investigations can occur to help reduce or eliminate the fraudulent claims/payments.
Even overpayments, one of the highest reasons for improper UI payments, can be detected by developing overpayment models using predictive analytics and machine learning technology. By running these models against weekly continued claims information, claimants can be flagged for follow-up or asked additional questions based on how likely the tool predicts they are to commit fraud. This allows state workforce agencies to detect fraud early on or even before payment is made.
States should consider Sagitec’s Neofraud™ solution. Neofraud™ is a fully integrated, browser-based software system with comprehensive functionality designed for predictive fraud detection in UI software solutions. States can configure Neofraud™ to create a model for managing and detecting fraud by both employers and claimants by evaluating their unique attributes. Tailor the attributes that define the propensity for fraud to meet your unique needs without complex software programming. Neofraud™ uses Neural Network Machine Learning (NNML) technology to flag fraudulent transactions and has unprecedented flexibility to evolve along with your organization, incorporating new features and functions as you see fit.
Neofraud™ was designed by industry veterans to dramatically improve fraud detection and identify overpayments for UI agencies. Neofraud™ can be implemented as a standalone system or integrated with your existing UI Tax and Benefit solution. And, it integrates seamlessly with Sagitec’s flagship Neosurance™ UI Tax and Benefit Solution. Neofraud™ will make it easy for users to define, train, evaluate, and execute the fraud model as well as analyze the results.
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Note: This blog has been edited.