AI and Big Data for a Revolution in Fraud Detection of Unemployment Insurance

Fraudulent claims within the unemployment insurance programs have often plagued governments worldwide, draining billions of dollars in public funds annually. Siddikur Rahman, a double MBA in Business Analytics and Management Information Systems, is attacking this critical challenge through innovative research that merges advanced technology with societal impact.

In his recent publication titled "The Role of AI, Big Data, and Predictive Analytics in Mitigating Unemployment Insurance Fraud," Rahman shows how AI and predictive analytics can flag fraud patterns with an incredibly high degree of accuracy. "Traditional detection systems often fall behind the sophisticated schemes of fraudsters," Rahman says. "But through the use of big data and machine learning algorithms, we can turn fraud detection on its head."

Rahman's framework unifies large datasets to find aberrations and anomalies, thereby providing governments with a powerful tool to fight inefficiencies and protect public funds. His research emphasizes the transformative potential of AI-driven solutions, not only in fraud prevention but across a wide range of applications in the public sector.

By fighting fraud, Rahman hopes for a future in which unemployment benefits are better distributed, resources are preserved, and public confidence in government systems is restored.

This cutting-edge research could serve as a blueprint for governments seeking innovative ways to modernize their systems and enhance accountability. Siddikur Rahman's work represents a significant leap toward a data-driven approach to social policy, where technology is not just a tool but a transformative force for good.