Journal of Economics Intelligence And Technology

Abstract: The growing complexity of the U.S. insurance industry has revealed the shortcomings of the traditional actuarial methods of assessing solvency, reserve adequacy, and systemic risk management. This integrative review, drawing on over 50 peer-reviewed articles, regulatory publications, actuarial standards, and institutional reports spanning 2019 to 2026, examines the impact of advanced actuarial modelling techniques, such as Principle-Based Reserving, stochastic modelling, machine learning, and systemic risk analytics, on risk assessment in the insurance and financial sectors in the United States. The review draws on evidence from three inter-related areas: solvency, reserve adequacy, and systemic risk. The results indicate that significant advancement has been made, especially in the improvement of risk sensitivity of capital adequacy assessment, more advanced stress testing of scenarios, improved identification of tail risk and emerging vulnerabilities, and increased precision of systemic risk monitoring at the entity and macroprudential levels. However, there are still challenges to be addressed in terms of model integration, regulatory consistency, and governance of emerging technologies. The review finds that the concepts of solvency, reserving, and systemic risk are interconnected, and approaches that consider them separately may not properly capture sources of vulnerability. More integrated actuarial frameworks are therefore needed to strengthen financial resilience, improve risk oversight, and address the structural changes reshaping the U.S. insurance sector.