Word count: 15000 words
Objectives to cover:
Introduction: Significance of fraud detection, role of data science, objectives, and scope.
Healthcare Insurance Fraud in Gulf Countries: Prevalence, types of fraud, regulatory frameworks, and current measures.
Application of Data Science in Fraud Detection: Machine learning, predictive analytics, big data integration, and real-time monitoring.
Challenges in Implementing Data Science: Data quality, regulatory constraints, legacy system integration, ethical concerns, and workforce limitations.
Strategic Approaches to Overcome Challenges: Policy recommendations, AI and blockchain adoption, data-sharing improvements, and capacity building.
Future Trends and Innovations: Explainable AI, federated learning, blockchain technologies, and AI-driven fraud detection prospects.
Conclusion: Summary of challenges, strategies, and future directions for fraud detection in Gulf healthcare.
Reference: APA style