Claims-based pricing is inevitable if insurers are to make a
healthy return. Otherwise, there is no
point in having these policies, or they would only be available to the very
wealthy. This is an issue of national
health policy that needs to be addressed.
The underlying problem is that we have an ageing population that is
living longer, meaning they will get a variety of critical illnesses. We do not have high enough fertility to
replace that ageing population, and subsidise the rising cost of their claims.
Singapore’s resident total fertility rate fell to a preliminary
0.87 in 2025, the lowest figure ever recorded in the country’s history, down
from 0.97 in both 2023 and 2024.
Replacement-level fertility sits at roughly 2.1 births per woman. Singapore has not touched that level since
1976. The proportion of citizens aged 65
and above nearly doubled in a single decade, from 13.1% in 2015 to 20.7% in
2025. The old-age support ratio, the
number of working-age citizens available to support each senior, collapsed from
7.4 in 2010 to just 2.4 in 2025. The
government’s own population projections show the citizen median age climbing
from 39 in 2011 to 47, and citizen deaths were projected to outstrip citizen
births by around 2025, the exact year that threshold arrived.
Why This is Not a Distant Actuarial Curiosity
An insurer pricing a critical illness policy today is pricing
against a population where, within a single working lifetime, the ratio of
contributors to claimants has fallen by two-thirds. Claims-based pricing is not insurers behaving
greedily. It is the only mathematically
honest response to a demographic base that can no longer absorb the cost of
pooled, flat-rate premiums the way it could when the support ratio sat above seven. A policy priced as though the 2010
demographic structure still held would either bankrupt the insurer or require
government subsidy at a scale no current budget accommodates.
Japan offers the clearest working example of exactly this
trajectory, having crossed the same demographic threshold roughly two decades
before Singapore. Japan’s own mandatory
long-term care insurance system, introduced in 2000 specifically because private
insurers and family caregiving could no longer absorb the cost of an ageing
population, has required repeated premium increases and benefit restrictions
since, precisely the pattern claims-based pricing exists to prevent from
happening chaotically rather than deliberately.
Singapore is not speculating about a future problem. It is watching a fellow high-income Asian
economy run the same experiment a generation ahead of it, and the results have
not been reassuring.
Why Immigration Policy Cannot be Separated from This
This is inevitably linked to immigration policy. We need more younger people becoming citizens
to address this demographic imbalance.
Otherwise, whatever measures we produce, even full government subsidy,
is inadequate to address the issue. In
short, we need more people contributing at the younger end of the pyramid to
afford the cost of healthcare for the older end. The government’s own scenario modelling
confirms this directly: every projection scenario that excludes immigration
shows the citizen population entering outright decline once deaths overtake
births, while every scenario incorporating sustained immigration materially improves
the old-age support ratio. There is no
version of this problem solved by domestic fertility recovery alone, not on any
timeline that helps the working-age population currently paying into the
system.
The Verdict
What we have now is a population mean of around 40 years old. It is barely manageable now. It will not be manageable in a decade. The fertility collapse to 0.87 and the
support ratio collapse to 2.4 are not warning signs anymore. They are the current operating conditions
insurers, policymakers, and immigration planners are already pricing against,
whether the public conversation has caught up to that reality or not.
Terence Nunis | Executive Chairman, Equinox Zenith | Author, The 1%
Playbook: The Billionaire Cheat Code

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