Mortality Trends and Its Impact on the Pension Liabilities
DOI:
https://doi.org/10.37965/jait.2024.0456Keywords:
mortality, pension liabilities, six-point lagrangian interpolation, big data processing, projected unit creditAbstract
Malaysia is forecasted to become an ageing nation by 2030. As this may reflect an improvement in the healthcare system, a lot of parties need to adapt to these changes immediately including the government, which is responsible for the wellbeing of the public sector employees by providing a defined-benefit scheme during their retirement. The study aims to perform big data processing and analyze Malaysian mortality trends by expanding the Malaysian Abridged Life Table for the past 20 years using the six-point Lagrangian interpolation method, which is a key machine learning algorithm used today. Apart from that, this study also aims to examine the impact of mortality changes on pension liabilities by using actuarial valuation methods, which is Projected Unit Credit (PUC) method. The sensitivity analysis will be conducted to observe the impact of the changes under five scenarios with four different ages at the time of valuation. Based on the empirical results, it was found that the Six-point Lagrangian interpolation method shows a satisfactory outcome as the error recorded is below 1 percent. The result shows that there is a decreasing pattern in the mortality rate for the past 20 years, which will eventually result in population ageing in Malaysia. Furthermore, the impact of reduced mortality rate on pension liabilities was also found to be significant. However, the impact can be mitigated by increasing the retirement age as life expectancy of the Malaysian population is believed to continue to increase due to ageing population.
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