Biological clocks aren't ready for insurers: what the data actually shows

The life insurance industry, historically ahead of the curve in anticipating therapies that treat aging, has rejected biological clocks as a mortality risk assessment tool because they simply don't perform better than conventional predictors: age, sex, smoking, blood pressure, BMI, and medical history. Epigenetic clocks—algorithms that estimate chronological age from DNA methylation patterns—are statistical models trained to minimize error across thousands of samples, not individuals. When applied to a single person, their estimates carry considerable biological noise and depend heavily on training populations; applying them to highly fit or self-selected individuals produces inaccurate predictions. For underwriters, the conclusion is definitive: while epigenetic age does predict mortality, it provides no discriminatory advantage over established metrics, except in narrow exceptions (young adults without traditional risk factors, or older adults with entirely negative markers). Without rigorous longitudinal analysis, these edge cases remain speculative, leaving the commercial longevity clock market as a promise without actuarial foundation.