<p>Mortality and life expectancy statistics have profound implications across diverse facets of society, including the financial, economic, and actuarial fields. Mortality is shaped by various factors, with income becoming a particularly critical determinant once age and sex have been accounted for. This paper proposes a new methodology for easily integrating income-related (contextual wealth) differential risks into death probabilities and (general and insured) life tables, showcasing its deep impact on financial and insurance products and risk management. The approach is based on estimating general population Income-Indices, whose estimation is illustrated via an extensive dataset composed of 253 million demographic events of the Spanish population. Employing the Income-Indices-based methodology in a competitive market emerges as a strategic advantage, positioning companies favorably compared with those adhering to conventional pricing methodologies.</p>

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Integrating Income-Indices into life insurance and financial products

  • Josep Lledó,
  • Jose M. Pavía

摘要

Mortality and life expectancy statistics have profound implications across diverse facets of society, including the financial, economic, and actuarial fields. Mortality is shaped by various factors, with income becoming a particularly critical determinant once age and sex have been accounted for. This paper proposes a new methodology for easily integrating income-related (contextual wealth) differential risks into death probabilities and (general and insured) life tables, showcasing its deep impact on financial and insurance products and risk management. The approach is based on estimating general population Income-Indices, whose estimation is illustrated via an extensive dataset composed of 253 million demographic events of the Spanish population. Employing the Income-Indices-based methodology in a competitive market emerges as a strategic advantage, positioning companies favorably compared with those adhering to conventional pricing methodologies.