Currently, the most common maximum issue age is 60. Only a few AU programs push their maximum issue age to 65 years. Medical impairments are more common at higher ages, which may correlate to lower acceleration rates and higher mortality slippage for policies issued to older applicants.
As shown in this chart, older applicants are less likely to be approved accelerated than younger applicants.
As one might expect, AU random holdout data reveals the highest mortality slippage for ages 40 and older. Interestingly, however, we see higher mortality slippage for ages 18-30 than the 31-40 age group. One theory is that people under 30 may visit their doctors less frequently than their older counterparts, and less detailed digital medical footprints may allow higher-risk, younger applicants who otherwise would have been disqualified from the accelerated process to be approved.
AU random holdout data reveals a material gender gap for estimated mortality slippage on AU policies. On average, the mortality slippage of females is 40% lower than the overall average for an AU program; the rate for males is 40% higher.
Early AU programs restricted offerings to preferred nontobacco user classes. But as the industry learned from its early iterations, AU programs have expanded to standard and better classes, both tobacco and nontobacco. Some programs are adding substandard classes to the mix, but they typically structure them as grouped substandard classes. In an accelerated environment where full details about the applicant’s health profile may not be available, it can be difficult to determine a precise table rating.
The best risk class has the highest acceleration rate and the highest mortality slippage. On average, the acceleration rate of the best risk class is between 1.5 and 2 times that of the residual standard class, as shown in Figure 3. Based on AU random holdout data, the best risk class has more than 1.5 times the overall mortality slippage level, on average. This is partly due to the absence of key metrics in traditional preferred criteria, such as measured cholesterol, blood pressure and build. Additionally, while other risk classes may benefit from “favorable misclassifications” in some programs, this isn’t possible for the best class because there are no better classes “upstream.”