The research explores the financial impacts of longevity risk on defined benefit (DB) pension plan liabilities in Ghana, utilizing data from the 2010 population census and the Lee-Carter model. It compares two key models: the traditional Lee-Carter model and an extended version. The backdrop underscores the global increase in life expectancy and the associated challenges for healthcare, pension plans, and the insurance industry. Methodology: The study employs the Lee-Carter model, a stochastic approach for mortality estimation and forecasting. Researchers introduce an extended model incorporating a needed exposure parameter. Data from Ghana's 2010 population census serve as the base, with the Lee-Carter model implemented using singular value decomposition (SVD) for estimation. Results: Analysis of mortality trends from Ghana's 2010 population census data reveals a significant decrease in mortality rates, indicating an increase in life expectancy among the Ghanaian population. Both the traditional Lee-Carter model and the extended version fit the data well, demonstrating their utility in mortality estimation and forecasting. The introduction of the needed exposure parameter in the extended Lee-Carter model provides valuable insights into exposures likely to result in a unit death case, enhancing the precision of benefit evaluations and product development. These insights aid in tailoring benefit structures within defined benefit pension plans and developing more customized and cost-effective products for insurance companies and pension plan schemes. Additionally, the analysis of the needed exposure parameter offers valuable insights into future liability considerations for pension plan schemes, helping trustees and fund managers better prepare for future financial obligations and ensuring the long-term sustainability of the pension fund. Conclusion: The study concludes that longevity risk significantly impacts the cost of pension liabilities in Ghana. The extended Lee-Carter model, incorporating the needed exposure parameter, enhances understanding of mortality trends. Trustees and fund managers of defined benefit schemes are recommended to assess their funds and adopt a Liability-Driven Investment (LDI) strategy tailored to their scheme's dynamics. The research emphasizes the need for managing longevity risk to ensure the long-term viability of pension funds. Impact of the research: The study contributes to understanding longevity risk in the context of DB pension plans in Ghana. The findings have implications for policymakers and practitioners in managing the effects of longevity risk. The introduced needed exposure parameter serves as a practical tool for insurance companies and pension plan schemes in product engineering, pricing, and future liability considerations. The research underscores the importance of incorporating longevity risk management strategies to ensure the financial sustainability of pension funds.