Economic Scenario Generators (ESGs) have become indispensable tools in modern insurance reserve valuation, solvency assessment, and asset-liability management due to their ability to model uncertainty in economic and financial variables. Despite their widespread application, there remains limited synthesized evidence regarding their design, calibration, regulatory application, and effectiveness in insurance liability valuation. This study presents a systematic literature review of ESG applications in insurance reserve valuation and liability risk measurement using the PRISMA 2020 framework. A comprehensive search of academic databases, regulatory publications, and industry reports covering the period 2000–2025 yielded 842 database records and 49 additional sources. Following screening, eligibility assessment, and quality evaluation, 85 studies were included in the final synthesis. The review identifies six major thematic areas: ESG architecture and calibration, regulatory and accounting requirements, reserve estimation for complex guarantees, computational techniques, model risk and validation, and emerging climate-related risks. Findings indicate a significant transition from traditional deterministic and single-factor models to sophisticated multi-factor, market-consistent stochastic frameworks driven largely by Solvency II and IFRS 17 requirements. Advances in proxy modelling, least-squares Monte Carlo methods, and machine learning have enhanced computational efficiency; however, challenges remain regarding the integration of real-world and risk-neutral measures, model validation, and climate risk incorporation. The study highlights critical research gaps and provides recommendations for future ESG development, regulatory harmonization, and robust insurance liability valuation practices.