The data is compelling: global population will likely peak sometime this century before beginning a sustained decline – a phenomenon unprecedented in modern history.

The Emerging Demographic Reality

The charts from the Global Aging Institute tell a compelling story. Most demographic models now predict global population peaking between 2064 and 2086, with maximum populations ranging from 9.7 to 10.3 billion people. What’s particularly notable is that newer projections tend to forecast earlier and lower peaks than older ones – suggesting that fertility decline is accelerating beyond previous expectations.

China represents perhaps the most dramatic example of this demographic shift. Once feared for its population explosion (internally and externally, but perhaps for different reasons), China’s fertility rate has plummeted to approximately 1.2 children per woman – far below the replacement rate of 2.1. China’s population peaked in 2020. The precipitous decline in fertility has already resulted in a decline in the population. Some models now suggesting its population could halve (or worse) by 2100 from its peak.

The Middle Income Trap and Demographic Headwinds

This chart illustrates what demographers call the “middle income trap,” where countries achieve middle-income status but struggle to join the ranks of high-income nations. Despite substantial growth in East Asia (6.4% annually) and South Asia (3.9% annually) between 1990 and 2022, their GDP per capita remains far below U.S. levels. Meanwhile, regions with lower growth rates like Middle East & North Africa, Latin America, and especially Sub-Saharan Africa (0.8%) show little convergence with developed economies. Sub-Saharan Africa has become relatively poorer relative to the US in the last 30 years.

A key insight here is that population dynamics may exacerbate this trap. Many middle-income countries are ageing rapidly before achieving high-income status – a phenomenon economists call “getting old before getting rich.” Sub-Saharan Africa as a region is almost unique in that it is still growing. But this rate is declining and the global pattern is clear.

This creates a challenging environment where countries must support ageing populations without the institutional and financial infrastructure that developed economies built during their demographic dividends.

Immigration: The Decisive Variable

This chart highlights immigration’s critical role in determining population trajectories in low-fertility environments. For the United States, the difference between the “zero immigration” and “high immigration” scenarios by 2100 is stark – 226 million versus 435 million people. This 209 million person difference exceeds the entire current U.S. population.

This reality transforms immigration from a purely social or political issue into a fundamental economic consideration. Countries with below-replacement fertility essentially face a choice: accept immigration or manage decline. Japan has largely chosen the latter path, while countries like Canada and Australia have embraced the former. The economic implications of these choices will shape national fortunes for decades.

Beyond GDP Growth: Rethinking Economic Impact

A recent conversation with a colleague raised an important question: Does population decline necessarily mean economic weakness? This requires nuanced analysis beyond simple GDP growth metrics.

The Debt Challenge

Population decline creates particular challenges for debt sustainability. With slower or negative population growth, overall GDP growth becomes more dependent on productivity improvements. This makes debt/GDP ratios harder to reduce through growth alone, potentially forcing difficult fiscal adjustments. While automation and technological advancement could boost productivity to offset population decline, experience suggests achieving sufficient productivity growth consistently is challenging.

Labor Market Transformations

An ageing, shrinking population dramatically alters labour market dynamics. While labour shortages may drive wage increases in certain sectors, they can also accelerate automation and reshape entire industries. Japan’s response to its demographic challenges provides valuable lessons, with its emphasis on robotics and technology reflecting adaptation rather than surrender to demographic destiny.

Consumption Patterns and Capital Markets

The traditional life-cycle theory of consumption suggests peak spending occurs in one’s 30s and 40s before declining in later years. However, emerging evidence indicates that aging societies develop different consumption patterns rather than simply reduced consumption. Healthcare, leisure, and personalized services become more prominent, while housing and transportation may decrease in importance.

For capital markets, the traditional view suggests an “asset meltdown” scenario as retirees liquidate investments. Yet the evidence for this remains mixed, with capital flows, policy interventions, and changing retirement patterns creating more complex outcomes than simple models predict.

Insurance Industry Implications

As an actuary, I see several potential implications for insurance markets in this demographically transformed landscape:

Long-Term Care Evolution

Increasing longevity combined with smaller families creates greater need for formal long-term care insurance, though significant challenges remain:

• Greater prevalence of LTC outside the US: As family sizes shrink, dependent ratios increase, and individuals live longer in retirement, Long Term Care (LTC) becomes an increasingly key product. LTC has had a difficult few decades in the US. It’s still fairly uncommon in emerging markets and even some developed markets. Early adopters in these markets can establish the brand, credibility, and experience to become a major player in this market as it grows.
• Hybrid Products: Traditional standalone LTC policies may give way to life/LTC or annuity/LTC hybrids that address the “use it or lose it” concern that has limited market acceptance.
• Home Care Focus: Products emphasizing aging-in-place technology and home care services rather than institutional care will likely gain prominence as consumer preferences shift.
• Public-Private Partnerships: The scale of the long-term care challenge may necessitate government involvement, with insurers potentially managing supplemental coverage above a public baseline.

Retirement Income Transformation

The traditional accumulation-to-decumulation retirement paradigm faces fundamental challenges:

• Flexible Drawdown Solutions: Products will need to accommodate phased retirement, part-time work, and variable income needs over potentially 30+ year retirement periods.
• Longevity Insurance: Advanced-age annuities that begin payments at 80 or 85 may become more prevalent as longevity risk pooling becomes essential for sustainable retirement planning.
• Integration with Healthcare: Retirement products that explicitly address healthcare cost uncertainty will become increasingly important, potentially with features that adjust income based on health status changes.

Investment and Risk Management Innovation

Traditional asset allocation approaches require rethinking:

• Extended Risk Horizons: Longer retirement periods necessitate maintaining higher equity allocations later in life, challenging conventional glidepath models.
• Real Asset Focus: Inflation protection becomes more critical with extended retirement periods, potentially increasing demand for real estate, infrastructure, and inflation-linked securities.
• Intergenerational Products: Multi-generational wealth transfer solutions that optimize across family units rather than individuals may emerge as family structures adapt to longevity.

Industry Structure Changes

Demographic shifts will reshape the insurance landscape structurally:

• Consolidation Pressure: Declining population in certain markets will reduce the absolute size of insurance pools, driving consolidation as fixed costs must be spread across smaller customer bases.
• Digital Transformation: Cost pressures will accelerate automation in underwriting, claims, and customer service, potentially turning insurance from a high-touch to a primarily digital industry.
• Scale vs. Specialisation: Large multinational insurers with the scale to invest in technology may have advantages, while specialized insurers focusing on specific demographic niches could also thrive.

Geographical Divergence

Insurance markets will increasingly bifurcate:

• Mature Markets: Rapidly aging countries will prioritize decumulation solutions, long-term care, and longevity protection.
• Growth Markets: Countries still experiencing demographic dividends will focus on protection, accumulation, and developing institutional capabilities.
• Cross-Border Opportunities: Insurers able to transfer knowledge between these divergent markets may develop competitive advantages through global learnings.

Addressing Behavioral Challenges

Demographic changes intensify existing behavioral biases:

• Longevity Underestimation: Products will need to address systematic underestimation of lifespan by consumers, potentially through novel framing of longevity risk.
• Cognitive Decline Protection: Financial products incorporating protection against diminished financial capacity in advanced age will become increasingly important.
• Family System Integration: Insurance solutions recognizing the role of family systems in later-life care and financial management will gain prominence.

Alternative Perspectives: Not All Decline

While I’ve outlined several challenges, it’s important to consider alternative viewpoints that paint a more optimistic picture of demographic change:

Productivity Growth as Compensation

As referenced earlier, technological advancement and artificial intelligence could potentially drive unprecedented productivity growth that more than offsets population decline. Countries like South Korea have maintained strong economic performance despite rapidly falling birth rates. The labor scarcity created by shrinking populations might accelerate automation and AI adoption, potentially unleashing productivity increases that our models currently underestimate.

Per Capita Prosperity vs. Total GDP

While total GDP might grow more slowly in shrinking populations, GDP per capita could still rise. Fewer people sharing national resources might lead to higher individual living standards, particularly if automation effectively addresses labour shortages. However, this doesn’t fully address debt sustainability issues – a challenge that might create incentives for moderate inflation to decrease the real value of accumulated public debt. Supply constraints from declining labour forces could contribute to such inflationary pressures.

It’s also worth questioning whether GDP per capita is even the right measure for societal wellbeing in aging societies. This metric excludes non-monetary aspects of wellbeing and non-remunerated work. An over-focus on GDP might misrepresent a future that includes many content retirees engaged in meaningful but economically unmeasured activities – from community service to artistic pursuits.

Environmental Benefits

A significant but often overlooked benefit of population stabilization or decline is reduced environmental pressure. Lower population could ease resource competition, reduce pollution, and potentially support more sustainable economic models. While climate change rightfully dominates environmental discussions, population stabilization represents one of the most effective (if slow-acting) approaches to reducing humanity’s ecological footprint.

The Japan Question

Japan’s experience with population decline provides a complex but instructive case study. Despite demographic headwinds, Japan has maintained relatively high living standards, low unemployment, and social stability. Their example suggests adaptation is possible, though not without trade-offs. Japan’s emphasis on automation, careful immigration, and social cohesion offers one path for other ageing societies.

Global vs. Local Asset Markets

While individual countries might mitigate asset price declines through global capital flows, the prospect of worldwide population aging raises questions about whether these balancing mechanisms will remain effective when most major economies face similar demographic trajectories simultaneously. This remains one of the great unanswered questions in demographic economics.

Adaptation Over Decline

Despite these challenges and opportunities, history teaches us that economies adapt. The 1950s comparison my colleague raised is instructive – economic structures reorganize around demographic realities. The key difference today is the direction of change: we’re entering an era where labor becomes more scarce rather than more plentiful.

This transition creates winners and losers. Countries and companies that successfully adapt to aging populations through technology, immigration, and institutional innovation will thrive. Those clinging to growth models predicated on expanding populations may struggle.

For actuaries and financial professionals, these demographic shifts demand fresh thinking about longevity risk, retirement adequacy, and intergenerational equity. Our traditional models built during an era of population growth require fundamental reconsideration.

The future may not be one of economic decline, but rather one of economic transformation – driven by demographic forces that are now firmly established and unlikely to reverse in the coming decades.

• Growing regulatory acceptance as parametric solutions prove their value. (Issues of insurable interest have posed problems. Currently in testing in “sandbox” regulatory environments in a few countries including South Africa, where it has traditionally been viewed as non-compliant.)
• Addresses previously uninsurable risks for corporates and governments, filling protection gaps. Good application for captive insurers (I’ll cover this more in a later post)
• Complements reinsurance by covering areas traditional policies often exclude
• Primarily used for commercial lines, but personal applications are emerging
• Significant applications for transferring country-level risk for governments and certain NGOs
• Basis risk remains a consideration, but can be mitigated somewhat through careful structuring

Exciting developments include parametric ETFs, allowing investors to participate in this innovative market. We’re also seeing creative applications using new data sources, like phone signals to assess footfall.

I can get theoretically excited about smart-contracts for parametric insurance, but in practice this quickly feels like unnecessary complexity with limited current benefit.

Parametric insurance can compete with reinsurance, but it’s often best used in combination, or as a tool for reinsurers to spread risk

As always, professional advice is crucial when exploring these solutions.

At a minimum, the contribution to group surplus/deficit Own Funds (in excess of, or the deficit where Own Funds don’t cover the SCR), should be shocked for currency risk. This makes sense as soon as you think about what the risk to the group’s SCR cover is on currency depreciation. (Where there is a deficit, foreign currency appreciation is the risk, not depreciation. The opposite is true – and more intuitive – when there is a deficit.)

The final answer is that ICS will likely not be applied to everyone in South Africa, but it may inform the development of SAM group reporting. It may also be the basis of choice for subsidiaries in other jurisdictions. ICS is probably more relevant than you thought.

I’ve had reasons to think about Nigeria recently, in general but also from an insurance market and acquisition environment. I’ve helped several investors looking at Nigerian insurers over the years. Familiarity with the market and the expectations of these investors has bred complexity rather than contempt. This isn’t an easy diagnosis of land of plenty or dystopian money pit.

Nigeria still presents a compelling opportunity with its expansive land, sizable population, youthful demographics, positive growth trajectory, and abundant natural resources. Beyond its renowned oil and agriculture sectors, Nigeria boasts a vibrant movie industry (Nollywood) and a robust financial services sector, albeit with banks making more headway than insurers. Wholesale and retail trade are the biggest contributors to economic growth. This dynamic mix showcases Nigeria’s diverse economic landscape and entrepreneurial spirit and an increased focus on the service sector over energy extraction and farming.

While Nigeria’s potential has long been evident, ongoing challenges test that optimism. 

Inflation (29.9% annual for January 2024) and currency depreciation (74% down against USD since January 2022) have impacted individuals and businesses, amplifying economic strains. The local impact of foreign currency denominated debt has ballooned due to Naira depreciation. Ghana’s recent default weighs on everyone’s mind.

Food security for many is now a significant risk. Infrastructure limitations persist, impeding the full realization of economic growth. High unemployment rates, coupled with security challenges and governance issues, have eroded public and investor trust. In the insurance sector, while some have some growth and success with new product lines, overall insurance penetration remains modest. Insurance adoption has not accelerated as rapidly as envisioned over the past decade or two

While Nigeria stands to gain from ongoing disruptions in the Middle East and related waterways, the nation’s oil and gas sector remains a double-edged sword—both a source of revenue and trouble. Given the historical challenges of theft and attacks on infrastructure, Nigeria may not be able to maintain let alone increase production to meet an increased demand.

The recent decision by Shell to exit Nigeria’s onshore oil sector highlights the substantial risks involved, not only to infrastructure but also to human life. As a significant portion of Nigeria’s economy is still reliant on the oil and gas sector, these developments raise concerns about potential prolonged challenges, affecting the economy and therefore adding headwinds to insurers growth aspirations.

Insurers can’t fix these challenges directly. They need to focus on perception and reputation, on paying claims and improving operational efficiencies. Some insurers are excited about mandatory health and pensions, to go along with mandatory cover for motorists, but these compliance push factors do little to promote trust in insurance unless servicing and claim payment are slick and reliable too.

Most of the growth that insurers have managed over recent years has related to growth in GDP rather than an increase in penetration. The sorts of sustained 20%+ real growth that attracts investors and revolutionises a market will not come from economic and population growth alone.

There are opportunities for growth. When someone cracks microinsurance distribution and costs, and reaps the rewards of brand awareness, that can unlock massive growth and profits over time. There are many uninsured vehicles that could be bought into the insurance net. Smaller group policies covering household help could meet a needs of employers and employees. Annuities are a growing product for some insurers, and may present a further way to accumulate assets and also demonstrate trust worthiness to the market. (On the flip side, a single failure of a provider of annuities will crush this market for decades.)

Insurers need to have a strategic plan to manage their business within the turbulent environment. Some of what’s needed:

• A focus on consolidation around key products, unsentimental views of product profitability and underwriting performance.
• Allocation of capital to products to demonstrate return on capital, or at least incorporating an appropriate cost of capital into performance measures.
• Clear separation of investment returns generated on shareholder assets when understanding operating performance. (Warren Buffet’s words can be on “the float” misconstrued to destroy shareholder value.)
• (While you’re at it, it’s way past time to carefully segregate portfolios and match or at least hypothecate assets to specific purposes.)
• Clear-eyed evaluation of participating products. Customer expectations, levels of fees and charges. Fair investment returns and bonuses. The aim is to grow trust over time and wealth for your policyholders. Performance for shareholders will come.
• In general, a greater proportion of premiums must be used for benefit payments to policyholders, distribution costs must be contained, and expenses must be decreased. This is necessary to drive customer value and build trust, while leaving space for returns to shareholders.
• A better understanding of the role and benefit of reinsurance in life insurance. Different structures and different retentions may provide better results than rolling over similar structures indefinitely.
• A Digital Distribution and Servicing Strategy than recognises the trust deficit insurers have to work with and constantly pushes that flywheel to build trust rather than just drive the next sale. Customers want ready access to policy information and up-to-date account balances and policy status. On the back end, a single view of customer is required, giving customers and servicing agents the ability to update details once – and then use those details for effective, useful communication to policyholders. The more self-service possible the more empowered customers will feel.
• Recognition that driving down unit expenses (per policy expenses) is necessary for profitability and customer value. And decreasing unit expenses requires economies of scale. And that economies of scale requires BOTH scale and low variable costs – which is a function of automation, Straight Through Processing, Standard Operating Procedures and streamlined products.

Nigeria presents an opportunity, but it’s not without risks. The time necessary to realise investment objectives may be longer than is palatable to many, and disinvesting in difficult times often leaves a bitter taste and a lightened pocket.

Focus areas will differ by entity, but based on my experience, the points above are a sensible starting point for most. Add the controversial elements of tax rule application consistency and greater market conduct regulation and Nigeria’s market could really begin to take off.

Business Rescue precludes creditors from applying for liquidation of the business. This is the removal of an existing right of lenders: “a temporary moratorium on the rights of claimants against the company or in respect of property in its possession”

From what I gather it’s not clear that this formally counts as default – might depend on specific loan or bond terms and how credit rating agencies respond to this.

How one “feels” about this is less relevant than the legal interpretation for cross-default provisions. It certainly feels like default to me.

For SAA, it’s also a step which means the government is no longer prepared to keep putting in money. That’s certainly a message about how likely any implicit (rather than explicit) governmental guarantees are for other entities.

Short aside on government debt and balance sheets

It’s not really so much that this is bad news, but rather this is the long-overdue recognition of how bad the news is around SOEs and their total contribution to the true Debt/GDP and their zero or negative contribution to the less-publicised Asset/GDP ratio. As I’ve mentioned before, another useful ratio would be (Debt-Assets)/GDP, which if measured carefully can be a more useful measure of the true financial position of a country and a better guide for decisions on whether to privatise an existing SOE.

A full balance sheet approach and one that considers return on capital (as well as also-important social-development, second-order, longer-term and positive externality items) should form a greater part of policy decisions.

I’m still working my way through the full report, but Kenya’s score is a significant jump above South Africa and the closely contested positions below it. Is Kenya genuinely making such inroads or is this a function of the measures used?

It’s not.

It’s also a good example of “actuarial sloppiness†.

To be specific, it is equally inappropriate if your current experience is a reasonable fit for the combined SA85/90 table.

SA85/90 was graduated based on South African insured lives data from 1985 to 1990. This period is important because it’s generally felt to be the last period in South Africa where HIV/AIDS would not have had a significant impact on mortality. (Estimates differ, but 1985 is often taken as the starting point for the HIV epidemic in South Africa and even though there might have been some deaths within the first five years, it is inconceivable to have affected a significant portion of the population.)

SA85/90 came in two version, “light† and “heavy†. Somewhat disappointingly, no distinction was made between males and females. Light mortality reflected the typical, historical, insured life characteristics which was pretty much white males. If I recall correctly, “Coloured† and “Indian† males were also combined into the light table. “Heavy† mortality reflected the growing black policyholder base in South Africa.

For all the awkwardness of this racial classification, the light and heavy tables reflect the dramatically different mortality in South Africa based on wealth, education, nutrition and access to healthcare. Combining the results into a single table wasn’t reliable since there were significant differences in mortality AND expected changes in the proportions of the heavy and light populations in the insured populations into the future.

A combined table was still created at the time. I suspect Rob Dorrington may have some regrets at having created this in the first place or at least in not having included a clearer health warning directly in the table name. The combined table reflects the weighted experience of light and heavy based on the relative sizes of the light and heavy sub-populations during the 1985 to 1990 period. I think a safer name would have been “SA85/90 arbitrary point in time combined table not to be used in practice†.

There is no particular reason to believe that the sub-population that you are modelling reflects these same weights. Even for the South African population as a whole these weights are no longer representative. The groups, at least in the superficial sense we view any particular citizen as coming from distinctly one group, will fairly obviously have experienced different mortality but will also have experience different fertility and immigration rates.

Our actuarial pursuit of separating groups of people into smaller, homogenous groups should also indicate that in most cases the sub-population you are modelling will more closely reflect one or the other of these groups rather than both of them.

But even if, just for the sake of argument, your sub-population of interest does reflect the same mix at each and every age as baked into the combined SA85/90 table, then it would still be entirely inappropriate to use the table for all but the crudest of tasks. After all, there a reason for our penchant for homogenous groups. If you model your sub-population for any length of time, the mix will surely change as those exposed to higher mortality die at a faster rate than those with low mortality.

The first order impact would be that you would be modelling higher mortality over time than truly expected. Due to the relative mortality between the two populations differing by age, the actual outcome will be somewhat more complex than that and more difficult to estimate in advance. This is particularly important with insurance products where the timing of death is critically important to profitability.

So, just because you can get a reasonable fit to your experience of an age- or percentage-adjusted SA85/90 combined table does not mean you have an appropriate basis for modelling future mortality. It may not vastly different from a more robust approach, but it’s just sloppy.

Messages? This time isn’t different, sovereign debt crises happen all the time, ignore currency risk at your peril and there are many reasons governments can default on their debt.

The message is that high growth economies don’t necessarily translate to high equity returns.

The argument can be summarised as this:

• Earnings growth is correlated with economic growth
• Valuation changes contribute significantly to equity returns and can have a major impact on equity returns distinct from underlying economic growth for long periods, 10 or 20 years
• But in the long term these valuation changes should even out. We should still be left with a correlation between economic growth and equity returns
• High growth economies need significant investment. This additional investment in companies comes at the cost of equity dilution. High growth economies are positively correlated with high dilution.
• Thus, EPS correlation with economic growth is significantly lower than it would be without dilution.
• This explains the virtually zero correlation between dividends and economic growth

Check out the full story for some pretty graphs.

What’s interesting for me here is that none of these arguments require or allow for market efficiency. It’s a totally separate way of looking at the issue with empirical evidence to support it.

I suppose the market efficiency counter would be that the change in valuation over long periods should be exactly as required to provide an appropriate risk-adjusted return to investors given the expected changes in all other variables. I don’t know if I buy that or not.

The key message for me is the counter argument to the “obvious” view that high growth emerging markets necessarily provide greater equity returns in the long run. The same can be said for why high growth companies don’t necessarily provide higher equity returns in the long run. As the low-growth companies are spitting out dividends to investors, the high-growth companies are diluting existing investors as they raise more capital.

The one question I haven’t full settled in my own mind is whether real dividends being correlated with economic growth is the best measure. High dividends now should result in low dividends in future. Low dividends now should result in high dividends in future. We should expect a point-in-time correlation between high growth economies (and companies) and low dividend yields. I would think that this correlation is needed in addition to the time series analysis performed by Dimpson, Marsh and Staunton since there can be weird lag effects that diminish the correlation there.

All the same, food for thought, especially living in a low-moderate growth emerging market country!