Understanding Health Insurance Fraud Risk in Universal Coverage Systems: A Global Scoping Review of Vulnerabilities, Detection Gaps, and System-Level Weaknesses

Background Health insurance fraud undermines service quality, equity, and the financial sustainability of Universal Health Coverage (UHC). While fraud is often perceived as an individual-level problem, emerging evidence points to systemic vulnerabilities—weak detection systems, limited governance capacity, knowledge gaps, and inadequate institutional controls—as key drivers. This scoping review maps the global evidence on fraud risk factors, detection gaps, and system-level weaknesses to understand how fraud evolves and persists within UHC and national health insurance systems. Methods A scoping review was conducted using Arksey and O’Malley’s methodological framework, refined by Levac et al., and reported in accordance with PRISMA-ScR guidelines. PubMed, Scopus, Web of Science, and Google Scholar were searched for studies published between 2014 and 2024. Studies examining fraud vulnerabilities, detection techniques, prevention strategies, or claims system weaknesses in UHC and national health insurance settings were included. Data were charted narratively and thematically across risk domains, detection approaches, and system-level determinants. Results Thirty-eight studies were included. Most focused on provider- or claim-level fraud detection using machine learning, anomaly detection, or data mining. However, the synthesis of system-level factors revealed consistent patterns of inadequate fraud resilience, including fragmented detection systems, limited data interoperability, weak institutional oversight, low provider billing literacy, a lack of structured fraud education, and insufficient integration of digital tools with governance mechanisms. The Forest plots illustrated that systemic vulnerabilities—such as complex claim structures, weak audit controls, governance gaps under pandemic stress, and black-box ML detection models—showed stronger associations with inadequate fraud system resilience than individual-level fraud factors. Evidence from LMICs, particularly Indonesia, highlighted how limited regulatory capacity and insufficient system readiness amplify fraud exposure. Conclusion Fraud within UHC systems is less a problem of detection failure and more a symptom of system-level fragility. Current approaches are reactive, detection-heavy, and insufficiently embedded within broader health system governance. Strengthening fraud resilience requires integrating structured fraud education, transparent digital surveillance, interoperable data systems, and proactive governance reform into UHC design. For LMICs, aligning technological innovation with systemic capacity-building is critical to ensure UHC remains equitable, accountable, and financially sustainable.