Social security analytics

Social security data analytics is the applications of data mining, knowledge discovery, machine learning, and broad data science in the areas of social security and social welfare. Relevant issues that can benefit from social security data analytics include understanding the underlying factors, reasons, scenarios, and intervention action responsiveness of overpayments, payment accuracy, and fraud; effective and efficient ways to prevent, predict and intervene overpayments and fraudulent behaviors.


Data-driven research and innovation has been shown valuable and effective to explore challenging issues in social welfare practices, and to develop workable systems, tools and case studies for strengthening government service objectives, improving service quality and policy making, enhancing the efficiency and effectiveness of social security/social welfare policies and processes.Moreā€¦