The social security system faces challenges in resource allocation, coverage, and efficiency. This study explores data integration methods, including behavior monitoring, fund tracking, and group identification, and proposes strategies such as classification, dynamic allocation, and policy adjustment. It also examines automated benefit calculation, service platform integration, and regional matching. The results improve data support and enhance system adaptability and efficiency.