In the life settlements industry, life expectancy (LE) providers are firms that conduct health underwriting toward predicting the future mortality of an insured. Multiple stakeholders are interested in evaluating the quality of their assessments. There has been some recent interest in better alternatives to the traditional metric for this quality, the A/E ratio: the ratio of actual to expected number of deaths. One such alternative is the implied difference in life expectancies (IDLE) metric proposed by Bauer et al. Its design largely retains the simplicity of the A/E ratio while being informative, unlike the A/E ratio, throughout the life of a policy block. Even though the IDLE is a significant improvement over the A/E ratio, it turns out that the IDLE is sensitive to departures from a key assumption, which motivates our development of a more robust metric. Our proposed methodology for evaluating the quality of the LE assessments involves using a survival regression model for estimating the mortality distribution of the insureds, with the average deviation of the life assessments from those derived using this model serving as a metric. In particular, we show that utilizing a Cox proportional hazards model with covariates derived from the LE assessments results in a robust yet well-performing alternative to both the A/E ratio and the IDLE.

在人寿结算行业，预期寿命 (LE) 提供商是进行健康承保以预测被保险人未来死亡率的公司。多个利益相关者有兴趣评估他们的评估质量。最近有人对这种质量的传统指标的更好替代方案感兴趣，即 A/E 比率：实际死亡人数与预期死亡人数的比率。一种这样的选择是预期寿命的隐含差异Bauer 等人提出的 (IDLE) 指标。与 A/E 比率不同，它的设计在很大程度上保留了 A/E 比率的简单性，同时在整个策略块的整个生命周期中都提供了信息。尽管 IDLE 比 A/E 比有了显着改进，但事实证明 IDLE 对关键假设的偏离很敏感，这促使我们开发更强大的指标。我们提出的评估 LE 评估质量的方法包括使用生存回归模型来估计被保险人的死亡率分布，并将寿命评估与使用该模型得出的平均偏差作为指标。特别是，